Search

Online and technology enhanced delivery are not conventional practices in art and design education and the attitude of design students towards this is largely underexplored. This research therefore explores the phenomenon of online learning and teaching in the context of Scotland's newest university, University of the Highlands, and Islands (UHI). The research evaluates existing provision of online learning and explores the potential of a blended or hybrid approach to learning and teaching as a future proposition within the context of the Creative Industries curriculum of the University of the Highlands and Islands (UHI). The research was undertaken with a view to inform UHI's future holistic and strategic approach to Creative Industries curriculum development; initial lecturer training; and to connect communities enabling wider access and collaboration within the Highlands and Islands of Scotland and internationally. The research reviews the blended learning and hybrid approach pre COVID-19, during and post the pandemic and the impact on future delivery of art and design education within UHI. The research reported here explored the development of learners' competences in online and blended design education in a longitudinal, qualitative study. The research discusses emergent themes such as roles of learner autonomy, communities, and networks. This thesis reviews theories and signature pedagogies in relation to art & design education whilst examining the potential of an optimum blended course. Creativity as a key competency forms a compelling rationale for the effective preparation of an 'optimum blend' of delivery related to art and design education. The findings in this thesis make a further persuasive case for hybrid and blended learning and teaching to be considered and designed. The thesis raises awareness of the benefits of art and design education in UHI and beyond. The findings present the hybrid studio as an interchange between internal and external factors in blended design education. Art and design students graduate and enter inspiring, sustainable, and fulfilling careers in the vibrant cultural and creative industries.

Humanisation (i.e., cultivating humanness and goodness in teaching and learning) is central to education. In modern times, when technology is reshaping our world, addressing humanness is especially important as we face crucial decisions regarding the quo Vadis of education and society. This study explored the pedagogical affordances of online technology through humanist-dialogic philosophical lenses. In this way, it became possible to get insight into what matters when we design for meaningful, rich and empowering online learning experiences coined as 'flow'. In particular, the research focused on exploring the relationship between learning experiences and design choices in a Small Private Online Course (SPOC) context to understand how we can teach and learn better in the Internet era. The study employed a design-based research (DBR) methodology incorporating three teaching experiments. The design framework for Teaching Experiment 1 was informed by the literature analysis about effective learning designs for MOOCs and SPOCs. The design frameworks for Teaching Experiments 2 and 3 (including intervention) were informed by design principles derived from Teaching Experiment 1 and the literature about dialogic learning. The data were collected from Business students at two Finnish universities using semi-structured interviews, an online questionnaire, and a feedback form. Analysis of the research data (using constant comparison and chiasm methods) produced a practical theory model called Humanisation of Online Learning (HOL). The HOL model suggests an innovative approach to creating 'flow' using four principles: (1) freedom, which describes learners' ability to pursue their preferences in learning in agreement with personal learning styles, goals, and situations; (2) care, which denotes learner's ability to make connections to the learning process and its participants ; (3) joy, which refers to learner's ability to stay enthusiastic and optimistic in learning; and (4) expansion, which concerns learners' ability to expand understanding of knowledge and themselves. The findings from this study provide a solid evidence base for future research and practice in online learning to benefit teachers, teacher educators, learning designers and institutional policymakers.

Videoconferencing platforms have been used for a number of years in the UK and other countries to facilitate instrumental music lessons between remote parties. However, videoconferencing is typically not optimised for music performance which results in poor audio quality and musicians not being able to play together. Prior to the COVID-19 pandemic, this led to some resistance to using the technology. Low-latency technologies such as LoLa and JackTrip offer high-quality audio and facilitate synchronous musical interaction so that remote parties can play music together in real time. However, limited research has been conducted on how effective these technologies are when used for instrumental music teaching. This study aimed to address this gap through the following research questions: • What changes in the quality of the interactions and the learning and teaching experience between face-to-face, standard videoconferencing, and low-latency environments? • Are some elements of music instruction more or less effective in these different environments? • What are the barriers to using these technologies in educational settings, and how can these be overcome? I deployed a mixed methods concurrent nested design. My research was primarily qualitative and conducted through a series of small-scale trials, interviews, and autoethnographic studies, together with analysis of data from a larger set of LoLa trials in three European conservatoires, and a small-scale quantitative study. Participants included music teachers and students in Higher Education and school settings across a range of instrument types and musical genres. Several themes emerged from a synthesis of the findings across the 17 studies, including: teachers' attitudes became more favourable to the various technologies after trialling them; the visual element of technologies was important for musical cues and diagnosing technical and postural problems in students; each learning environment had its own advantages and disadvantages, but participants preferred the face-to-face environment. My research makes an original contribution to literature by reporting findings showing that: playing together can form a significant element of face-to-face lessons, LoLa and JackTrip low-latency technologies improved musical interactions compared to standard videoconferencing platforms, LoLa can be used in conjunction with an institutional firewall, JackTrip can be used with multiple players on domestic internet connections. I conclude that low-latency technologies have an important role in the future of music education by offering increased interaction between teachers and students from different institutions, and by offering new teaching and learning possibilities, including collaborative learning, and teaching through playing.

In our data-driven society, personal data affecting individuals as data subjects is increasingly being collected and processed by sizeable, international companies. While data protection laws and privacy technologies attempt to limit the impact of data breaches and privacy scandals, they rely on individuals having a detailed understanding of the available recourse, resulting in the responsibilisation of data protection. Existing data stewardship frameworks incorporate data protection considerations and employ data-protection-by-design principles but may not include data subjects in the process itself, relying on supplementary legal doctrines to strengthen data protection enforcement. Current data protection solutions also lack support for protecting individual autonomy over personal data through co-creation and participation, particularly where there is socio-technical and communal value to collaborative data from which data subjects may not currently benefit. These challenges motivate the application of a theoretical and practical framework that can encourage co-creation of data protection solutions, increase awareness of different stakeholder interests, and rebalance power between data subjects and data controllers. In this thesis, we propose adapting the commons framework to create a data protection-focused data commons. We conduct interviews with commons experts to identify the institutional barriers to creating a commons and challenges of incorporating data protection principles into a commons. We propose requirements for establishing a data protection-focused data commons by applying our interview findings and data protection principles. We then deploy the data protection-focused data commons using an online learning use case. We conduct a study to explore the usefulness of the commons for supporting students' agency and co-creating data protection solutions in response to tutorial recordings, their consent preferences, and attitudes towards privacy and online learning. We find that a data protection-focused data commons as a socio-technical framework can support the collaboration and co-creation of data protection solutions for the benefit of data subjects.

The study investigated the perceptions the acceptance and continued use of e-LMS for teaching and learning in South African ODeL university. A quantitative research method using a cross-sectional design was deemed appropriate to collect data that answered the research questions of this study. Two questionnaires were designed to be completed by both academic staff and first year students of a language department. The Unified Theory of Acceptance and Use of Technology (UTAUT) was adopted as the theoretical framework underpinning this study while Bourdieu's concept of habitus, capital and field and constructivism were used as philosophical underpinnings. The findings of this study clearly indicate that despite e-learning being in its infancy in this ODeL university and South Africa in general, students and academic staff are already using the e-LMS for learning and teaching respectively. However, facilitating conditions and technological habitus which include e-LMS system overload, poor bandwidth, high data costs, minimal participation of both academic staff and students, among others, still bedevil the implementation of e-learning within the South African ODeL context. Structural equation modelling was also used to test UTAUT constructs and found that all constructs had no relationship with behavioural intention. However, age, experience and computer access were moderating variables. The findings of the study contribute to the body of knowledge on the use of UTAUT in the South African ODeL context. More importantly, the study contributes a framework for acceptance and continued use of e-LMS for ODL universities in the context of developing countries.

Non-stationary streaming data poses a familiar challenge in machine learning: the need to obtain fast and accurate predictions. A data stream is a continuously generated sequence of data, with data typically arriving rapidly. They are often characterised by a non-stationary generative process, with concept drift occurring as the process changes. Such processes are commonly seen in the real world, such as in advertising, shopping trends, environmental conditions, electricity monitoring and traffic monitoring. Typical stationary algorithms are ill-suited for use with concept drifting data, thus necessitating more targeted methods. Tree-based methods are a popular approach to this problem, traditionally focussing on the use of the Hoeffding bound in order to guarantee performance relative to a stationary scenario. However, there are limited single learners available for regression scenarios, and those that do exist often struggle to choose between similarly discriminative splits, leading to longer training times and worse performance. This limited pool of single learners in turn hampers the performance of ensemble approaches in which they act as base learners. In this thesis we seek to remedy this gap in the literature, developing methods which focus on increasing randomization to both improve predictive performance and reduce the training times of tree-based ensemble methods. In particular, we have chosen to investigate the use of randomization as it is known to be able to improve generalization error in ensembles, and is also expected to lead to fast training times, thus being a natural method of handling the problems typically experienced by single learners. We begin in a regression scenario, introducing the Adaptive Trees for Streaming with Extreme Randomization (ATSER) algorithm; a partially randomized approach based on the concept of Extremely Randomized (extra) trees. The ATSER algorithm incrementally trains trees, using the Hoeffding bound to select the best of a random selection of splits. Simultaneously, the trees also detect and adapt to changes in the data stream. Unlike many traditional streaming algorithms ATSER trees can easily be extended to include nominal features. We find that compared to other contemporary methods ensembles of ATSER trees lead to improved predictive performance whilst also reducing run times. We then demonstrate the Adaptive Categorisation Trees for Streaming with Extreme Randomization (ACTSER) algorithm, an adaption of the ATSER algorithm to the more traditional categorization scenario, again showing improved predictive performance and reduced runtimes. The inclusion of nominal features is particularly novel in this setting since typical categorization approaches struggle to handle them. Finally we examine a completely randomized scenario, where an ensemble of trees is generated prior to having access to the data stream, while also considering multivariate splits in addition to the traditional axis-aligned approach. We find that through the combination of a forgetting mechanism in linear models and dynamic weighting for ensemble members, we are able to avoid explicitly testing for concept drift. This leads to fast ensembles with strong predictive performance, whilst also requiring fewer parameters than other contemporary methods. For each of the proposed methods in this thesis, we demonstrate empirically that they are effective over a variety of different non-stationary data streams, including on multiple types of concept drift. Furthermore, in comparison to other contemporary data streaming algorithms, we find the biggest improvements in performance are on noisy data streams.

Recommender systems play a vital role in how any well functioning website presents content to users. With the amount of content growing day by day, the ability to accurately hone in on the specific interests of any given user has taken on an ever increasing significance. In this thesis we investigate the application of a handful of techniques that are aimed at improving how content is presented to users in online environments. Two major real-world use cases are discussed: the recommendation of adverts on AutoTrader and the recommendation of news articles on the BBC website. Throughout the thesis emphasis is placed on the use and development of algorithms which scale to these real world use cases. The structure is a follows: Chapters 2 and 3 set out the groundwork for the major advances in this area and ensure that the knowledge required for topics in later chapters are available for the reader; these are predominantly focused on the multi-armed bandit problem and the variation inference algorithm. Chapter 4 describes the development of a new hybrid algorithm, FAB-COST, which seeks to leverage two moment matching variational inference algorithms, namely Expectation Propagation and Assumed Density Filtering, to build a procedure which is both accurate and able to handle steaming datasets. Its superior performance is demonstrated by benchmarking it against another state of the art contextual bandit algorithm using real user click data from the Auto Trader website. Chapters 5 and 6 demonstrate how recommendations can be improved at BBC News via Collaborative Topic Models. The fact that users have a strong preference towards recently published news, as well as the data pipeline the BBC have in place, means that cold-start presents a serious problem when making news recommendations. By incorporating contextual information present in the articles into the recommender system, articles that have no user histories associated with them can be recommended to users -- a task that traditional collaborative filtering algorithms are unable to fulfil. We give an in-depth mathematical and empirical analysis of the algorithms, as well as a detailed account of how they have been and can be used in a real world setting. We provide codes which demonstrate that the Collaborative Topic Model provides superior recommendations qualitatively and quantitatively, and importantly, works with the current infrastructure the BBC have in place.

This thesis outlines an evolving understanding of online postgraduate healthcare education and proposes a pedagogical model to conceptualise the process. It draws together six peer-reviewed publications on the subject and highlights how understanding of this area of education has improved as a result of this work. This form of teaching is evolving rapidly and is currently undertheorized and lacking a secure evidence base. A total of 91 in-depth research interviews were carried out, with educators, learners and graduates during the individual studies affording a good oversight of online postgraduate healthcare education. Online postgraduate education is conceptualised as situated at the boundaries of professional and academic spheres, offering a potentially democratic learning environment for both educators and learners. Learning is described as a horizontal process, allowing the sharing of learning and expertise between academic and professional environments to occur. Learning is recursive as students combine their professional work while studying part-time. Many online postgraduate learners are mid-career professionals with established professional networks and this helps to explain the impact of such studies that can extend far beyond the individual learner into their wider professional practice. This work challenges the notion that online learning is social impoverished. When well designed and delivered online postgraduate education can offer profound learning opportunities, however, there is a need for academic staff who are experienced in online teaching to share their expertise more widely. Technology is merely a tool that allows human interactions and does not enhance learning without human agency. The current instrumental focus on quality within higher education risks regarding online postgraduate degrees solely in terms of their income generating potential. This focus on finance overlooks the educational potential of such programmes of study as well as the academic challenges in delivering high quality programmes. Commonly held views that online postgraduate recruitment can be scaled up without significant academic effort and additional resources are countered.

This study argues that student to student conversations in groups have a significant impact on learning. Previous studies have focused on the potential impact of individual contributions in these learning conversations. This study challenges this view and suggests that measuring these individual contributions cannot, on their own, improve the student experience and impact on student performance. A case study design was used to explore what was happening in an online collaborative group task. This was achieved by examining the dialogic interactions in asynchronous online discussions being used in the group collaborative process. The dataset for this investigation was a large corpus of online posts by eight postgraduate student groups working on a group task. The data was analysed using framework analysis. Developed by Richie and Spencer (1994), framework analysis is a matrix based method which allows the researcher to demonstrate how the data was managed and allows the researcher to move back and forth between different levels of abstraction whilst still keeping sight of the "raw" data. The central component of framework analysis is the development of a thematic framework. This thesis also examined quantitative data related to the number, length and frequency of discussion posts within and across each of the groups. Overall a typology of three dialogic types were identified and ten key characteristics of these groups were also identified. This thesis found that the predictive value of monitoring the use of time was very low if this is the only indicator used. The dialogic types identified in the findings were found to be significant. Their presence or absence in the group communications had the potential to help educators predict whether the group would go on to meet the criteria for the task in the time allocated. The group characteristics also contributed to this prediction and there appeared to be a cumulative effect the more characteristics that were present. This suggests that the group conversations had a significant impact on individual and group achievement. The findings of this thesis have significant implications for how we understand student to student interactions and their impact on learning. This study has used online student group conversations. However, the findings do not only have impact for student conversations in online learning but relate to all forms of learning. Revealing the impact of these interactions to educational designers and teachers can help support students in group learning. In addition, if students understand the impact group conversations have on their learning and achievement and that of their peers, sharing this information has the potential to significantly improve their performance and learning experience. This study recommends further research be carried out into student to student dialogue to explore further how learning is impacted by group conversations. It is recommended that this exploration should focus on theory generating research to help address the theoretical gaps that exist in understanding how students learn in collaboration with each other. This should be utilised to enhance student experience, performance and achievement.

This study explored widening participation [WP] in higher education [HE] by investigating the views and experiences of students, their parents, teachers and University staff, in a pre-entry to HE programme. The research focussed on researching the influence of a Pathway Opportunity Programme [POP] on students' aspirations, preparedness and learning for university, with consideration of the most valuable aspects of the POP, alongside how it could be improved. Other ways to widen participation and help to overcome barriers to HE were also explored. In order to discover participants' views to obtain a better understanding of their experiences, the research study used the Capabilities Approach as a conceptual framework. A mixed methods design was utilised, with data collection through semi-structured interviews and online surveys. The challenges of 'insider' research was discussed, and the Capabilities Approach employed to thematically analyse and interpret the data. The study found that their experiences of the pre-entry programme impacted positively on participants' aspirations for HE with increased confidence, motivation, and decision-making. The study also observed that participants improved their preparedness for university, with the residential and online learning components particularly aiding the transition to HE. Regarding the effect on student learning, the study reports an increase in participants' non-cognitive, affective skills. In addition, the study found the most valuable aspects of the POP are the insight it provides into the university experience, the incentives offered, and the positive impact on communication skills and motivation. Improvements to structural aspects of the programme are also presented. Furthermore, the study reports four areas which could advance WP in HE: earlier intervention, tutoring, financial incentives, and partnerships. The thematic analysis and resultant sub-themes make an original contribution to the field by expanding Walker's application of the capabilities approach to WP in HE.

While short-term interactions with robots benefit from the novelty effect, long-term interactions can suffer from a decrease in user interest and engagement. Based on the previous research within Human-Robot Interaction (HRI), the thesis presented here is that user experience in long-term human-robot interactions can be improved by personalising the interaction through recognising users and recalling previously learned information. User recognition is the first step towards personalising the interaction, however, there does not exist a reliable user recognition method for fully autonomous user recognition in long- term HRI for real-world applications. Correspondingly, this thesis proposes a Multi-modal Incremental Bayesian Network (MMIBN) model, which combines face recognition with soft biometrics and allows continuous, incremental and online learning of users, without the need for any preliminary training. We validated the robustness and reliability of this approach with a long-term (4-weeks) real-world study with 14 users and an artificially generated multi-modal long-term user recognition dataset with 200 users. Following on from this work, we explored personalisation of the interaction in service robotics and socially assistive robotics, based on earlier evidence for the impact of personalisation on long-term interactions. We created the text-based Barista Datasets that contain simulated generic and personalised dialogues for interactions with a barista that recall and suggest user preferences in subsequent interactions in a coffee shop. Based on these datasets, we designed fully autonomous barista robots with MMIBN, automatic speech recognition (ASR) and a rule-based dialogue manager, and evaluated these robots with a real-world long-term (5-day) study with 18 non-native English speakers. The study demonstrated that personalisation mitigates negative user experiences that arise from unreliable speech recognition and the inflexible structure of the rule-based dialogue manager. Consequently, we explored the potential of the state-of-the-art data-driven dialogue models based on the Barista Datasets. The results showed that while data-driven models perform remarkably well in generic task-oriented dialogue, no model could perform sufficiently well for personalisation in long-term interactions. Lastly, to demonstrate the real-world bene ts of long-term HRI, we design a personalised robot to improve user motivation and adherence to the cardiac rehabilitation programme, and evaluate with a study that ran for 2.5 years at a hospital in Colombia. The robot individually tracked the patients’ health progress and attendance throughout the programme, and provided personalised and immediate feedback based on continuous monitoring for 18 weeks. While the study could not be completed due to the outbreak of COVID-19, our initial findings (with 6 patients) showed that user engagement and motivation for the therapy and adherence were improved and maintained in the long-term interactions. Overall, the work undertaken provides supporting evidence for our thesis and contributes fundamental stepping stones for future research in personalised long-term HRI to develop robots that can meet and maintain user expectations.

The legacies of colonial rule continue to impact everyday life, particularly in education. These structural inequalities are often reinforced and amplified in online ‘global’ education through a form of digital neocolonialism, which is where hegemonic powers indirectly control or influence marginalised groups through the internet or information technology. In striving for justice-oriented online education models, this study analyses to what extent Massive Open Online Courses (MOOCs), produced both internationally and locally, support (or could support) the needs, preferences, and aspirations of marginalised South African youth and address the material, cultural-epistemic, political, and geopolitical injustices they face. To evaluate what South African peri-urban youth desire in their education and futures, as well as the challenges they experience, a seven-part survey was conducted with 250 youth from five townships in South Africa. Responses showed that whilst participants strongly value and aspire to further their education, financial difficulties, infrastructural barriers, family problems, and lack of emotional support and life mentorship limit them from achieving this. Participants reflected on how colonial and apartheid legacies have affected their educational experiences and identities through inferior quality of education, forced languages, forgotten histories and incongruent values, cultural norms and practices. In parallel, semi-structured interviews were conducted with 35 MOOC designers, from South Africa and the USA, to investigate the ways in which efforts, if any, were being made to reach students most in need of quality education. Interviews covered themes of openness, accessibility, and justice. It was found that, depending on the MOOC designer’s understanding of social justice and decolonial thought, they placed varying emphasis on addressing different forms of injustice. Some focused on resource, access and infrastructural barriers, while others focused on issues of content relevance and knowledge production. Furthermore, MOOC designers’ attempts to address injustices strongly related to their own identities and lived experiences, highlighting the importance of plurality of thought and epistemic diversity in the producers of MOOCs. Drawing on the historical injustices and lived experiences of the youth, and the attempts to address injustices by the MOOC designers, it was ascertained that there is no one size-fits-all formula to creating equitable MOOCs. Rather, depending on the purpose and target audience of the MOOC, nuanced approaches to addressing injustices are suggested. These approaches are shaped by various leverage points that influence the types of, and the extent to which, participatory methods, accessibility measures, knowledge sources, assessment and critical pedagogy are implemented. Additionally, the importance of these leverage points varies over the MOOC’s lifecycle, from inception and design, to implementation and assessment. Bearing in mind the broad-ranging injustices that youth participants raised, these approaches are presented with great caution that educational technologies and open education are not panaceas but if designed and used appropriately and justly, can be tools for liberation.

Similarity matching (SM) is a framework introduced recently for deriving biologically plausible neural networks from objective functions. Three key biological properties associated with these networks are 1) Hebbian rules, 2) unsupervised learning, and 3) online implementations. In particular previous work has demonstrated that unconstrained-in-sign SM (USM) and nonnegative SM (NSM) can lead to neural networks (NN) performing linear principal subspace projection (PSP) and clustering. Starting from USM and NSM, the work undertaken in this thesis 'explores' capabilities and performance of SM and 'extends' SM to novel sets of NNs and unsupervised learning tasks. The first objective of this work is to explore the capabilities of existing SM NN for feature learning. Representations learned from different SM NN are used as input to a linear classifier to measure their classification accuracy on established image datasets. The NN derived from NSM is employed to learn features from images with single and dual-layer architectures. The simulations show that features learned by NSM are comparable to Gabor filters and that a simple single-layer Hebbian network can outperform more complex models. The NN derived from USM is used for learning features in combination with block-wise histogram and binary-hashing. The proposed set of architectures (USMNet), when evaluated in terms of accuracy, shows competitive against unsupervised learning algorithms and multi-layer networks. Finally, Deep Hebbian Networks (DHN) are proposed. DHN combines within one architecture stages of NSM and USM. The performance of DHNs are evaluated on image classification tasks and outperforms the aforementioned models. The second objective of this work is to extend SM beyond linear methods and static images. To incorporate nonlinearity, kernel-based versions of SM, K-USM and K-NSM, are proposed and map onto NNs performing nonlinear online clustering and PSP, outperforming traditional methods. To incorporate temporal information, a new SM cost-function is applied to pairs of consecutive images to develop the TNSM algorithm. This is mapped onto a NN that performs motion detection and recapitulates several salient features of the fly visual system. The proposed approach is also applicable to the general problem of transformation learning.

This study aimed to investigate the Wiki teacher's role in a collaborative writing environment using a Web 2.0 tool, Wiki. Besides that, the Wiki teachers' perception on using Wiki technology in their collaborative writing classes was sought after as well as the challenges that they faced through the five Wiki classes. The study took place in the CPS in the SQU. It was conducted by two EFL teachers who were a male and a female. Being an observer and an interviewer in a qualitative case study research, I utilised two main research instruments including observations and semi-structured interviews. The findings revealed that teachers had a positive attitude of using Wiki in a collaborative writing class. The findings also revealed that the Wiki teachers showed six main roles which were managerial roles, Wiki teacher as assessor, social roles, pedagogical roles, technical roles and psychological role. In their managerial roles, the Wiki teachers carried some preparations before the Wiki class. They included assigning students in groups and assigning group leaders for each group. The roles included also organizing the Wiki class work which included dividing the work among students' and watching group leaders' work. In their technical role, the Wiki teachers were to facilitate students work on Wiki, train students how to use Wiki, and use online materials to assist students' work on Wiki. More interestingly, the study findings showed a technical cooperation between the Wiki teachers in which they exchanged their experience when teaching on Wiki. In their social role, the Wiki teachers were deducted through teacher to students' interaction (T-S), which was observed throughout the Wiki five projects. Being an encouraging Wiki teacher, it led to student to student interaction, (S-S), to take place through students' interaction on Wiki. Teacher's presence encouraged (S-S) interaction which led also to other reasons that enhanced interaction between students (S-S). The Wiki teachers as assessors could be deducted as the Wiki teacher's ability to let students comment and give feedback on each other's work. It also focused on the Wiki teacher's feedbacks, comments and rewards for students work in a Wiki environment. At the end of the Wiki classes, the Wiki teachers asked students to reflect upon the five Wiki lessons they did. In their pedagogical role the Wiki teachers were first and foremost teachers who would enable students to grasp pedagogical goals of learning on Wiki. Besides that, the Wiki teachers facilitated learning on Wiki for their students through pre and during Wiki classes. In pre-Wiki classes, the teachers made some pedagogical preparations which were used to prepare to the next Wiki classes and design course materials. Through during-Wiki classes, the Wiki teachers prepared pedagogical activates which differentiate between types of teaching and learning. In the psychological roles, the Wiki teachers showed personal motives, leading motives, mental motives and emotional motives when teaching collaborative writing using Wiki technology. Finally, the study investigated the challenges that a Wiki teacher faced in a Wiki environment. These challenges were linked to the students' readiness to work on Wiki as well as some technical problems. There were some other challenges, caused by different factors. At the end of the study, my thesis recommends some further studies. They are to open new doors for new studies, based on the study findings. They are also to reflect on the limitations of the current study.

How can real robots with many degrees of freedom - without previous knowledge of themselves or their environment - act and use the resulting observations to efficiently develop the ability to generate a wide set of useful behaviours? This thesis presents a novel framework that enables physical robots with many degrees of freedom to rapidly learn models for control from scratch. This can be done in previously inaccessible problem domains characterised by a lack of direct mappings from motor actions to outcomes, as well as state and action spaces too large for the full forward dynamics to be learned and used explicitly. The proposed framework is able to cope with these issues by the use of a set of local Goal Babbling models, that maps every outcome in a low dimensional task space to a specific action, together with a sparse higher level Reinforcement Learning model, that learns to navigate between the contexts from which each Goal Babbling model can be used. The two types of models can then be learned online an in parallel, using only the data a robot can collect by interacting with its environment. To show the potential of the approach we present two possible implementations of the framework, over two separate robot platforms: a simulated planar arm with up to 1, 000 degrees of freedom, and a real humanoid robot with 25 degrees of freedom. The results show that learning is rapid and essentially unaffected by the number of degrees of freedom of the robot, allowing for the generation of complex behaviours and skills after a relatively short training time. The planar arm is able to strategically plan series of motions in order to move its end-effector between any two parts of a crowded environment, within 10, 000 iterations. The humanoid robot is able to freely transition between states such as lying on the back, belly, and sides, and occasionally also sitting up, within only 1, 000 iterations. This corresponds to 30 − 60 minutes of real-world interactions. The main contribution of this thesis is to provide a framework for solving a control learning problem, previously largely unexplored with no obvious solutions, but with strong analogies to, for example, early learning of body orientation control in infants. This thesis examined two quite different implementations of the proposed framework, and showed success in both cases for two different control learning problem.

Online education has the potential for radically altering the field of education within our lifetime. Unfortunately, too many programs are being developed as a cost saving measure with little regard to the pedagogical needs of this emergent field. If this field is to develop in such a way that it meets the needs of the future generations, it must be grounded in theories of learning and motivation. This paper describes a research study of behavioral intentions to use a virtual learning environment for international high school students. Unlike many other earlier technology acceptance studies, it is grounded in a rich motivational theory of learning: Selfdetermination theory. The study also includes a new conceptual diagram, the Motivation Enhanced Technology Acceptance (META) Model to study of the phenomenon of technology acceptance from a motivational perspective. This is a Design-based research study and, as such, has both practical and theoretical goals. It seeks to refine theories of technology acceptance and use by grounding them in Self-determination theory. It also seeks to provide a usable solution to guide practitioners in designing online course.

This PhD research investigates the significance of learners' profiles on the implementation of online learning systems. Using Brunei Darussalam as its research context where online learning implementation is at its infancy and with 73.7% of its young population having been identified as ‘digital natives', this research explores the diversity in the student population based on their dispositions and how these dispositions influence their learning effectiveness. A series of systematic literature reviews on preceding student-profiling practices and three pilot studies precursory to this research suggested that the learner population comprise of multidimensional and heterogeneous individuals whose dispositions interplay and dynamically change. Utilising Pierre Bourdieu's theory of practice as an all-encompassing theoretical framework, 407 learners from the Brunei technical vocational education student population were holistically profiled into different learner types. The research adapted a sequential transformative mixed-method design with its data collection methods comprising of a self-designed quantitative questionnaire called the Online Learner Profiling questionnaire and a sequential series of qualitative interviews. Data from the questionnaire was analysed using Exploratory Factor Analysis that identified 7 possible habitus types and several variant types based on a 6-factor model. Subsequently, data from the interviews was inductively and deductively analysed through a Two-Cycle Coding Method that established the differences between habitus types as well as similarities between members of the same type. Abductive inferencing generated detailed descriptions of the 7 main habitus types based on their dispositions and the probable online learning tools, approaches and affordances that can be incorporated in online learning systems to complement their dispositions. The research discourse extends to a hypothetical projection that there are 64 possible habitus types. Collectively this theory has been given the name the Habitus Lattice Theory due to the habitus types interconnecting into a lattice. The profiling of students is anticipated to prepare educators and policy-makers in the implementation of online learning systems revolving around the issues of 'hysteresis' whereby online learning systems do not complement students' dispositions; the relevance of 'conatus' whereby students dynamically move from one habitus type to another; and the reduction of 'doxa' which are predetermined and oftentimes conjectural perceptions of who the online students are. Ultimately, the utilisation of Bourdieu's theory as a profiling mechanism provides a more holistic and possibly novel alternative to the many existing learning models and inventories that are used in understanding students' learning preferences.

With the increasing pace of technological changes in the modern society, there has been a growing interest from educators, business leaders, and policymakers in teaching important higher-order skills which were identified as necessary for thriving in the present-day globalized economy. In this regard, one of the most widely discussed higher order skills is critical thinking, whose importance in shaping problem solving, decision making, and logical thinking has been recognized. Within the domain of distance and online education, the Community of Inquiry (CoI) model provides a pedagogical framework for understanding the critical dimensions of student learning and factors which impact the development of student critical thinking. The CoI model follows the social-constructivist perspective on learning in which learning is seen as happening in both individual minds of learners and through the discourse within the group of learners. Central to the CoI model is the construct of cognitive presence, which captures the student cognitive engagement and the development of critical thinking and deep thinking skills. However, the assessment of cognitive presence is challenging task, particularly given its latent nature and the inherent physical and time separation between students and instructors in distance education settings. One way to address this problem is to make use of the vast amounts of learning data being collected by learning systems. This thesis presents novel methods for understanding and assessing the levels of cognitive presence based on learning analytics techniques and the data collected by learning environments. We first outline a comprehensive model for cognitive presence assessment which builds on the well-established evidence-cantered design (ECD) assessment framework. The proposed assessment model provides a foundation of the thesis, showing how the developed analytical models and their components fit together and how they can be adjusted for new learning contexts. The thesis shows two distinct and complementary analytical methods for assessing students’ cognitive presence and its development. The first method is based on the automated classification of student discussion messages and captures learning as it is observed in the student dialogue. The second analytics method relies on the analysis of log data of students’ use of the learning platform and captures the individual dimension of the learning process. The developed analytics also extend current theoretical understanding of the cognitive presence construct through data-informed operationalization of cognitive presence with different quantitative measures extracted from the student use of online discussions. We also examine methodological challenges of assessing cognitive presence and other forms of cognitive engagement through the analysis of trace data. Finally, with the intent of enabling for the wider adoption of the CoI model for new online learning modalities, the last two chapters examine the use of developed analytics within the context of Massive Open Online Courses (MOOCs). Given the substantial differences between traditional online and MOOC contexts, we first evaluate the suitability of the CoI model for MOOC settings and then assess students’ cognitive presence using the data collected by the MOOC platform. We conclude the thesis with the discussion of practical application and impact of the present work and the directions for the future research.

Online examinations are an integral component of many online learning environments and a high-stake process for students, teachers and educational institutions. They are the target of many security threats, including intrusion by hackers and collusion. Collu-sion happens when a student invites a third party to impersonate him/her in an online test, or to abet with the exam questions. This research proposed a profile-based chal-lenge question approach to create and consolidate a student's profile during the learning process, to be used for authentication in the examination process. The pro-posed method was investigated in six research studies using a usability test method and a risk-based security assessment method, in order to investigate usability attributes and security threats. The findings of the studies revealed that text-based questions are prone to usability issues such as ambiguity, syntactic variation, and spelling mistakes. The results of a usability analysis suggested that image-based questions are more usable than text-based questions (p < 0.01). The findings identified that dynamic profile questions are more efficient and effective than text-based and image-based questions (p < 0.01). Since text-based questions are associated with an individual's personal information, they are prone to being shared with impersonators. An increase in the numbers of chal-lenge questions being shared showed a significant linear trend (p < 0.01) and increased the success of an impersonation attack. An increase in the database size decreased the success of an impersonation attack with a significant linear trend (p < 0.01). The security analysis of dynamic profile questions revealed that an impersonation attack was not successful when a student shared credentials using email asynchronously. However, a similar attack was successful when a student and impersonator shared information in real time using mobile phones. The response time in this attack was significantly different when a genuine student responded to his challenge questions (p < 0.01). The security analysis revealed that the use of dynamic profile questions in a proctored exam can influence impersonation and abetting. This view was supported by online programme tutors in a focus group study.

Under the pressure of federal accountability for high schools in the United States to improve and maintain high rates of on-time graduation, online credit recovery has become an increasingly popular intervention to help students earn credit in a course that they have previously failed. While some studies have connected online credit recovery with positive outcomes for participants, others have found negative outcomes and poor learning experiences. Set in a large school division in Virginia, the purpose of this study was to (a) identify explanatory student factors that were associated with participation in online credit recovery and (b) compare the likelihood of on-time graduation of participants with the likelihood of on-time graduation of nonparticipants. Limited to the graduation cohorts of 2019 and 2020, there were 10,010 students in the sample from the participating school division. In the sample, 27% of students were eligible to participate in online credit recovery, but only 2.3% of students participated. Binary logistic regression models were designed to identify factors associated with participation and the likelihood of on-time graduation. Covariates considered for inclusion in the model were gender, race and ethnicity, status as an English learner, status as a student with a disability, status as homeless, status as economically disadvantaged, high school grade point average, and school. Both models failed to meet goodness of fit standards and were rejected as having fit the data. No student factors were found to have explained participation, and differences in the likelihood of on-time graduation were not identified. These findings indicated that there did not appear to be systemic participation given the studied factors, reinforced by the finding that participation was relatively uniformly distributed among the schools. The finding of a lack of significant difference in the likelihood of on-time graduation highlighted flexibility for schools in choosing their recovery interventions. State agencies may also consider collecting and publicly reporting data about student participation in online credit recovery. Opportunities for future studies include replication in other settings, particularly districts of different size and area/region, and qualitative inquiry into decisions made by school and district leaders related to credit recovery.

The purpose of this case study was to understand first-year college students’ perspectives on online discussion boards in the context of learning, via the community of inquiry framework. The theory guiding this study is Lev Vygotsky’s sociocultural theory, which identifies how learners create their own learning experiences in the classroom. The theory’s value comes from it being used to understand student thought in discussion boards, which is the study’s focus. A case study was the design, and the goal was to gather empirical data from discussion board experiences from students. The central research question was What are the experiences of a group of first-year nontraditional students engaged in a discussion board for a virtual English composition course? Fourteen students, 13 females and one male, made up the sample. Their discussion board responses, individual interviews, and group study recordings represent the qualitative data. All data were collected in a virtual setting via the online classroom, as well as Zoom. Interpretational phenomenological analysis was employed to analyze student interview responses, the group study, and discussion board responses to uncover themes in the data. The study found four significant themes during the analysis phase. First, the participants took little satisfaction in the social presence in the discussion board due to a lack of social opportunities. However, the participants did enjoy instructor presence, thanks to quick, encouraging, and critical responses. In addition, the participants did not exhibit a sense of critical thinking and seemed to participate with mostly the minimum requirement. It is hoped this research will act as a foundation for additional exploration into the community of inquiry’s relationship with online learning by providing starting points for answers to the issue of online student engagement.

This study investigated the effects of online learning on mental health. The focus included six aspects: academic performance, physical activity, social isolation, food insecurity and other stressors, pros and cons, and religion and mental health. Each aspect included advantages and disadvantages that adolescent students experienced. The study included 6th - 12th graders attending a Charter school. The eligibility requirement was that participants participated in online learning during the 2020-2021 school year. Academic performance data was obtained from the school office for students who attended the school during online learning and requested from parents if they attended other schools. Both positive and negative effects of factors were obtained using online questionnaires, which were reviewed during in-person interviews to investigate what challenges students experienced and how online learning effected mental health. Parents of student participants and current teachers were recruited and administered a short questionnaire to obtain their perspectives and observations of the six aspects. Results showed that students adapted and used alternative methods to limit negative issues to mental health. Academic performance was maintained, despite students feeling they struggled. Physical activity and food insecurity and other stressors were not a noticeable issue. Students reported both pros – flexibility, sleeping in, self-paced schedule - and cons – social isolation, technology glitches, lack of teacher connection. Students showed resiliency and self-initiative attitudes in finding alternative methods to persevere through the cons. Social isolation was reported as the most negative. Religion and mental health was not a factor in negative/positive effects.

The purpose of this qualitative phenomenological study was to understand and describe the essence of the experiences of teachers who have taught physical education remotely. The problem is physical education is a core curriculum subject that is designed for in-person instruction and is not easily adaptable to an online setting. The central research question that this study sought to address was what are the experiences of K-12 physical education teachers who taught P.E. remotely? The theory guiding of this study is Dabrowski’s theory of positive disintegration as it details how people can adapt and adjust in response to stressful situations and adverse events. I chose a phenomenological research method with an exploratory focus. This study was vital to understanding the experiences of teachers who taught physical education in a remote setting. This type of design was most appropriate for this study because understanding the perspectives of the participants was important to be able to identify the unique challenges of the group being studied. The sample size was 10 participants from schools across the United States who have taught physical education remotely for at least one year in a traditional K-12 school. The data collection included answers from the individual interview questions, and information gathered from the focus groups and questionnaires. To analyze the data, I used a form of manual coding. I looked for themes and patterns and significant statements. I then created a list of non-overlapping statements about how the interviewee experienced the phenomenon being studied. This information was used to draft answers to the research questions. The findings indicated that although teaching physical education remotely is challenging, teachers can adapt and find creative ways to address these challenges in order to provide the best possible educational experience for the student, even when teaching physical education remotely.

Abstract This qualitative research study explores high school teachers' perceptions of the factors influencing their self-efficacy during emergency remote teaching (ERT) in response to the COVID-19 pandemic. The study, conducted in a New Jersey high school, investigates the immediate transition from traditional in-person instruction to fully remote learning. By utilizing semi-structured interviews, the research focuses on five emergent themes: Adaptability and Flexibility, Student-Centered Approach, Communication and Transparency, Resourcefulness and Connection, and Challenges and Uncertainty Management. The research study aligns with Albert Bandura's self-efficacy theory, examining how mastery experiences, vicarious experiences, social persuasion, and physiological arousal contribute to teachers' self-efficacy during ERT. The findings suggest that teacher self-efficacy manifests in diverse forms. The research reframes teacher self-efficacy as adaptable and amenable to strategic cultivation, providing a comprehensive framework for promoting, supporting, and nurturing diverse facets of self-efficacy in the face of unprecedented challenges. This research study contributes valuable insights for K-12 administrators, offering qualitative data to inform future planning, preparation, and implementation of best practices during emergency school shutdowns. The multifaceted understanding of teacher self-efficacy presented in this research underscores the importance of recognizing and cultivating diverse forms of self- efficacy for sustaining effective teaching practices. Keywords: self-efficacy, emergency remote teaching, COVID-19 pandemic, online learning, teaching, learning

With the continual decline of high school graduation rates in South Carolina, there is a need for high schools to look at alternative pathways to graduation. Many of the current alternatives offered to students remove them from the high school setting or interactions with the student body. This study focused on an alternative pathway to graduation, Students Willing and Ready to Motivate to Graduate (SWARM), offered at the high school during the regular school day to students in jeopardy of not graduating. This inclusive approach eliminated transportation barriers and access issues. Students attended school regularly, but one to four classes per day were in the SWARM classroom. In this SWARM classroom, students used a web-based learning management system to complete self-paced courses needed for graduation. These courses were supervised by a certified teacher and had instructional support from content-based teachers. In addition, students in the SWARM program had the opportunity to participate in in-person classes, including career and technology courses, Naval Junior Reserve Officer Training Corps (NJROTC), fine arts, performing arts, and athletics. An improvement science study was conducted to determine if students in the SWARM program could earn credits faster than in the traditional classroom to accumulate the credits needed to graduate on time. Stakeholders were surveyed to gauge support and opinions about the program and to guide future PDSA cycles. The study found that implementing the SWARM program helped students in jeopardy of not graduating, and they were able to earn the necessary credits to graduate on time, including several who graduated early in December. Survey results indicated stakeholders are pleased with the program and want it to continue.

This thesis comprises a critical review and suggestions for enhancement of the Community of Inquiry Framework (CoIF), the frequently cited model of collaborative community-based online learning. It combines a systematic engagement of relevant literature and research, with the application of the CoIF thinking to six of my peer-reviewed publications. Although not initially conceived as forming part of a doctorate submission, these publications are drawn upon throughout this narrative, to assist my interrogation of the CoIF. They are also used to provide evidence of my continuing journey as an education researcher. This thesis is therefore not an exegesis – a traditional meta-narrative encompassing this candidate’s publications. It moves beyond my findings in the publications to create and present supplementary concepts, and develop pointed guidance about using the Framework in supporting online learning in tertiary education. My review first critically interrogates the three constituent elements or Presences of the CoIF. Social presence emerges as a highly complex and multi-faceted construct, in which the de-emphasising of the affective in the CoIF seems at variance with current research reporting the strong student emotional response to working online, and particularly in collaborative, community-based groupings. Then, in Cognitive presence, there has been little consideration of, and specificity about, reflection in the CoIF. My critique proposes that reflection and critical thinking are distinct but inter-related concepts; both of which need to be addressed. Teaching presence is renamed ‘Tutoring presence’ informed by my review based upon my emergent understandings of student-centred learning. Two enhancements to the CoIF are then proposed, together with the rationale for establishment of a Tutors’ Network. The first enhancement, referred to as 'the Influences,’ unites and enriches the individual Presences. The second argues for the existence and use of a personal learning retreat at the heart of a community of inquiry, addressing a perceived omission in the CoIF. This learner ‘space’ provides a ‘quiet, safe place’ for the private (internal) world of the learner, as a foil to the shared collaborative space in the CoIF (the external world). Finally, a Tutors’ Network is outlined as a vehicle for advancing their understandings and knowledge of online, collaborative, community-based learning in general, and in particular of communities of inquiry. This should develop the abilities of online tutors, improve their learners’ educational experiences and encourage research and scholarship into the CoIF.

Telecare and especially Mobile Care Systems are getting more and more popular. They have two major benefits: first, they drastically improve the living standards and even health outcomes for patients. In addition, they allow significant cost savings for adult care by reducing the needs for medical staff. A common drawback of current Mobile Care Systems is that they are rather stationary in most cases and firmly installed in patients’ houses or flats, which makes them stay very near to or even in their homes. There is also an upcoming second category of Mobile Care Systems which are portable without restricting the moving space of the patients, but with the major drawback that they have either very limited computational abilities and only a rather low classification quality or, which is most frequently, they only have a very short runtime on battery and therefore indirectly restrict the freedom of moving of the patients once again. These drawbacks are inherently caused by the restricted computational resources and mainly the limitations of battery based power supply of mobile computer systems. This research investigates the application of novel Artificial Intelligence (AI) and Machine Learning (ML) techniques to improve the operation of 2 Mobile Care Systems. As a result, based on the Evolving Connectionist Systems (ECoS) paradigm, an innovative approach for a highly efficient and self-optimising distributed online machine learning algorithm called MECoS - Moving ECoS - is presented. It balances the conflicting needs of providing a highly responsive complex and distributed online learning classification algorithm by requiring only limited resources in the form of computational power and energy. This approach overcomes the drawbacks of current mobile systems and combines them with the advantages of powerful stationary approaches. The research concludes that the practical application of the presented MECoS algorithm offers substantial improvements to the problems as highlighted within this thesis.

Education has always required the use of tools and resources to effectively impact learners. The creation of these tools, or modalities, requires advanced knowledge of design and an understanding of the needs of the users. Designers can use contemporary research on technology, inclusivity, and accessibility to develop impactful learning modalities.Written, visual, and multimodal content are explored in this research. Four digital web-responsive educational modalities (essay, quick text, infographic, and interactive) were created all providing the same information about tectonic plates. Users were randomly assigned a modality and then given as much time as needed to view or interact with it. When finished, they filled out a survey about their demographics, their comprehension of the information from the modality, and information about their educational experiences. While modality type did not impact users’ comprehension scores, it was found that demographic information could play a role in users’ abilities to understand scientific content. Adults with STEM (science, technology, engineering, and mathematics) careers and children with an adult in the household with a STEM career performed better on the comprehension section than those not frequently exposed to STEM topics. Additional demographic information was analyzed, and standard deviations show that the additional information did not impact scores. By understanding what demographic details impact user education, better educational resources can be designed to accommodate user needs.

The demand for online education has significantly increased in recent years, prompting many educational institutions to consider its continued adoption in many ways. However, some faculty members have encountered challenges in teaching online due to a lack of adequate training and guidance on effective online teaching practices. This study aims to provide evidence-based guidance for higher education instructors in selecting effective instructional strategies in online learning environments. It employs design and development research methodology to create instructional strategy selection guidelines for online courses in higher education. The guidelines, rooted in pedagogical approaches, are designed to assist faculty in selecting appropriate instructional strategies for online learning. They comprehensively outline the various instructional strategies and the factors influencing the decision-making process for selecting instructional strategies in online learning environments. The study makes contributions to research and content development by providing strategy selection guidelines for quality online education.

This qualitative research phenomenological study examined the lived experiences of 13 adult English Language Learners (ELLs) involved in online learning in a community-focused college between 2020 and 2022. The study, through surveys and semi-structured interviews, empowered participants by giving voice to their experiences and views regarding online learning. Analysis of participants’ data revealed four themes: the significance of exploring learner experiences, engagement in learning environments, fostering self-directed learning, and addressing online learning challenges for adult ELLs. These themes were comprehensively discussed using three theoretical frameworks: Andragogy, Constructivism, and Second Language Acquisition. The findings from this study emphasized the important implications of stakeholders addressing the needs of adult ELLs and providing them with a supportive learning environment that fosters their growth in English proficiency.

The purpose of this quantitative, nonexperimental causal-comparative study was to determine if there is a difference in student academic outcomes among elementary and secondary students who participate in online learning whose parents have favorable perception ratings of virtual learning and those whose parents do not. Understanding the influence of environmental factors on a student’s academic achievement, including persons close to the student, provides a conceptual framework for the direct impact of parental satisfaction with educational experiences on student performance in the online learning environment. The Panorama Family-School Relationships Survey was used to measure overall parental perceptions of the online learning environment and pedagogical practices. A convenience sample of 139 parents from a target population of students who were enrolled in virtual instruction through their local school district in central Virginia for the most recently completed school year (2022-2023) were surveyed for this online causal-comparative study. A two-way analysis of variance (ANOVA) was started to analyze the data collected. The assumption of normality and assumption of homogeneity of variance was not met. The data was strongly negatively skewed and was transformed. Due to assumption violations with the original and transformed (logarithmic and inverse) data, the Two-Way ANOVA was not completed. Visual analysis of the data collected for this study supports the theory that parental satisfaction with the learning environment continues to be a factor influencing student academic outcomes in post-pandemic education, where virtual instruction has become an established option to traditional face-to-face learning.

The purpose of this hermeneutical phenomenological study is to understand the experiences of low-income students in an online learning environment and how they are socially and academically integrated at an institution in southwest Georgia. Tinto’s 1997 revised student integration model and theory on how institutions must socially and academically integrate students to improve students’ persistence is to guide this research. The participants for this study are ten low-income students who participated in the data collection tools, which are surveys, focus groups, and individual interviews. The participants expressed their experiences, barriers, social and academic integration, and persistence in an online learning environment. The data is analyzed using Moustakas’ 1994 seven-step modification of the van Kaam method, which developed themes and patterns to understand the experiences of low-income students participating in an online learning environment. After analysis, the three themes formed (1) barriers to success, (2) overcoming barriers and persistence, and (3) integration. The results of this investigation were consistent with the current studies on the experiences of low-income students.

The purpose of this transcendental phenomenological study was to describe science faculty’s experiences with change as they transitioned from using traditional laboratories to using non-traditional laboratories at postsecondary institutions. The theory that guided this study was the transtheoretical model of change, as it explains the processes of change the faculty may have gone through as they transitioned from using traditional laboratories to non-traditional laboratories. A transcendental phenomenological qualitative design was used with a sample of 10 purposely selected post-secondary science faculty members to answer the study’s central question: What are the shared lived experiences of science faculty transitioning from traditional laboratories to non-traditional laboratories at post-secondary institutions? Data collection included semi-structured interviews with each participant, a sample of a non-traditional laboratory exercise chosen by the participant, and a semi-structured focus group discussion forum. Moustakas’s transcendental phenomenological data analysis triangulated the pertinent themes found through reduction, horizonalization, and imaginative variation. There were four themes identified in the study: support during the transition, the effects of infrastructure on the transition, the faculty’s change in role during the transition, and the faculty’s embracement of change.

The purpose of this transcendental phenomenological study is to discover the asynchronous online learning experiences that support learning motivation for community college degree-seeking non-traditional adult learners in the United States. The theoretical framework guiding this study is Knowles’ andragogy adult learning theory. The utilization of Moustakas’ analysis of transcendental phenomenology utilized epoché, or the removal of personal bias, and the focus of Moustakas’ bracketing of the central research question. The central research question is: How do community college degree-seeking non-traditional adult learners experience motivation in the asynchronous online learning environment? The study consisted of 10 degree-seeking non-traditional adult learners who completed an asynchronous online course for degree credit at a community college in the United States. Data collections utilized Moustakas’ data analysis to discover the essence of the phenomena utilizing three data collections: feedback surveys, interviews, and letter-writing. The research data was synthesized using summarized composite descriptions and triangulation.

The use of machine learning to predict output from data, using a model, is a well studied area. There are, however, a number of real-world applications that require a model to be produced but have little or no data available of the specific environment. These situations are prominent in Intelligent Environments (IEs). The sparsity of the data can be a result of the physical nature of the implementation, such as sensors placed into disaster recovery scenarios, or where the focus of the data acquisition is on very defined user groups, in the case of disabled individuals. Standard machine learning approaches focus on a need for training data to come from the same domain. The restrictions of the physical nature of these environments can severely reduce data acquisition making it extremely costly, or in certain situations, impossible. This impedes the ability of these approaches to model the environments. It is this problem, in the area of IEs, that this thesis is focussed. To address complex and uncertain environments, humans have learnt to use previously acquired information to reason and understand their surroundings. Knowledge from different but related domains can be used to aid the ability to learn. For example, the ability to ride a road bicycle can help when acquiring the more sophisticated skills of mountain biking. This humanistic approach to learning can be used to tackle real-world problems where a-priori labelled training data is either difficult or not possible to gain. The transferral of knowledge from a related, but differing context can allow for the reuse and repurpose of known information. In this thesis, a novel composition of methods are brought together that are broadly based on a humanist approach to learning. Two concepts, Transfer Learning (TL) and Fuzzy Logic (FL) are combined in a framework, Fuzzy Transfer Learning (FuzzyTL), to address the problem of learning tasks that have no prior direct contextual knowledge. Through the use of a FL based learning method, uncertainty that is evident in dynamic environments is represented. By combining labelled data from a contextually related source task, and little or no unlabelled data from a target task, the framework is shown to be able to accomplish predictive tasks using models learned from contextually different data. The framework incorporates an additional novel five stage online adaptation process. By adapting the underlying fuzzy structure through the use of previous labelled knowledge and new unlabelled information, an increase in predictive performance is shown. The framework outlined is applied to two differing real-world IEs to demonstrate its ability to predict in uncertain and dynamic environments. Through a series of experiments, it is shown that the framework is capable of predicting output using differing contextual data.

This thesis offers an assessment design for collaborative learning, utilisation of blended learning support through current communication technologies and highlights the crucial role of the tutor. The thesis designed and tested a theoretical framework which encompassed an active learning environment and resulted in the development of the shamrock conceptual framework. To test the theoretical framework, clarify the role of the tutor and the impact on the learner experience two studies were undertaken using pedagogical models that combined the concepts of learner-centric, sociocultural and dialogic perspectives on collaborative learning and technology in meeting the needs of learners in the 21st Century. In the first study, the role of the tutor was found to be crucial in setting, implementing and guiding learners using the assessment design as part of a social constructivist pedagogical practice. The pedagogical approach adopted was to blend face-to-face and Wiki learning experiences and was found to promote learner ownership, engagement and the fostering of a learning community. The second study validated the first and provided additional asynchronous technology experiences in addition to the Wiki blend in the assessment design. Study 2 examined the role of the tutor and the learner whilst using current technologies comprising podcasts and video and a Wiki in the collaborative experience. Findings showed that the Wiki supported community and collaborative aspects of a sociocultural practice whilst learners were engaged in authentic learning activities and led to a well supported learning environment. The importance of technology design and use to accommodate collaborative and community aspects was found to be an essential component. It was found that technology is not simply an add-on but rather needs to be planned and considered purposefully by both tutors and learners when used in a blend to supplement learning on campus as part of an assessment design in higher education. This study has shown that, for this to happen, academics need to be provided with the appropriate support, knowledge and skills required in developing a blended learning experience using a Wiki supplemented by class contact on campus as part of an assessment design.

In this thesis an architecture, similar to subsumption architectures, is presented which uses low level behaviour modules, based on combinations of machine learning techniques, to create teams of autonomous agents cooperating via shared plans for interaction. The purpose of this is to perform effective single plan execution within multiple scenarios, using a modern team based first person shooter video game as the domain and visualiser. The main focus is showing that through basic machine learning mechanisms, applied in a multi-agent setting on sparse data, plans can be executed on game levels of varying size and shape without sacrificing team goals. It is also shown how different team members can perform locally sub-optimal operations which contribute to a globally better strategy by adding exploration data to the machine learning mechanisms. This contributes to the reinforcement learning problem of exploration versus exploitation, from a multi-agent perspective.

This submission sets out a narrative of how a practitioner in the field of education identified and implemented the changes required, both in research methodology and in practice, in order to answer the question ‘how do I improve my practice?’ (Whitehead and McNiff, 2004) while remaining true to a personal value system by not teaching or researching in ‘a living contradiction’ (Ibid: 5) where a value system and a practice are not working in harmony. This submission chronicles a self-study journey to improve practice by identifying and reflecting on the changes required to improve that practice when ‘teaching’ ten-year-old pupils historical enquiry online. The narrative demonstrates how a practice can be reconceptualised and illustrates the outcomes of that re-conceptualisation. The particular practice in question was set within the context of technological advances in the Internet over the last half decade: in the early research the pupils used the Internet as an online encyclopaedia while in the later stages of the research they used the Internet as a means to access online authoring sites on the read-write resource Web 2.0. The journey of change follows the practitioner from teaching historical enquiry within a classroom setting to that of teaching historical enquiry within an online authoring site, called a wiki. To achieve those changes many key concepts (that had informed teaching practices at the beginning of the research journey) had to be deconstructed and subsequently restructured using an alternative design. The learning process was one of the key concepts teased apart and reconstructed using Wenger’s ‘communities of practice’ approach as a template for designing a small community of practices. It was the emerging small community of practices on the wiki that developed into a new perspective on how to promote the learning process most effectively in an online context. The submission also narrates the ontological dimension to the journey where the practitioner’s key personal values were used in the change process to create a living theory. This value driven methodology created living standards of judgement. The submission identifies, then critically reflects on, the two voices representing the significance of the developing perspectives of the writer as researcher and as practitioner. It then uses journal entries, articles and interviews to follow the practitioner journey from perspective point one to perspective point two. It reflects critically on the change process being experienced and the growing confidence that emerged as the practitioner and researcher voices began, in combination, to challenge accepted practice and develop a new single voice that impacts upon both the professional context and the field of educational theory. It leads to the acceptance of some of Wenger’s assertions that underpin his notion that meaning is negotiated in communities of practice and examines the changes in thinking that eventually led to this model being interpreted as a reference point only and to the suggestion of a new perspective on the learning process. The contribution to knowledge is, then, to be found in this new perspective of what is meant by a community of practices and the learning processes it generates with reference to teaching historical enquiry skills to ten-year-old pupils on an online authoring site called a wiki.

This thesis investigates personal knowledge development in online learning environments and the impact that personal values have on it. Personal knowledge development was investigated from the perspective of Nonaka’s SECI model of organisational knowledge creation. This model served as the basis for an adapted model that conceptualises personal knowledge development in online learning at the individual level. The personal value types of the Schwartz Value Survey and the Portrait Values Questionnaire were adopted to measure personal values and their impact on personal knowledge development in online learning environments. Three data collection approaches were used. First, an exploratory study was conducted which elicited online learners’ experiences of their personal knowledge development in online learning; this study used online discussion forums for data collection. Second, a Delphi study was carried out. Experts were asked which of the ten individual-level value types by Schwartz are likely to be particularly relevant in the context of online learning. Third, an online survey was created. Its aim was to measure the impact that personal values and background variables, such as gender and age, have on personal knowledge development in online learning. A measurement instrument was devised that measures three of the SECI modes, namely Externalisation, Combination and Internalisation. This instrument measures the magnitude of online learners’ Externalisation and Combination activities as well as their level of Internalisation, i.e. the outcomes of personal knowledge development. Results of the exploratory study show that there are widely diverging experiences of personal knowledge development in online learning. The literature review suggests that the cultural situatedness of an online learning environment is an important influencing factor on personal knowledge development. The results of the Delphi study suggest that Self-Direction, Stimulation, and Achievement are particularly relevant value types in the context investigated here. Finally, the online survey confirms this view, as all three value types were found to be positively correlated with Externalisation, Combination, and Internalisation, with the exception of the Achievement-Combination relationship. A modified version of the SECI model is proposed, which extends the applicability of the original SECI model from the organisational to the individual level. It is argued that this model is suitable to describe personal knowledge development in the context of online learning. The study also contributes to closing the gap in research on the impact of personal values in the context investigated in this study. Moreover, a measurement instrument was created that can be used to measure Externalisation and Combination, i.e. personal knowledge development processes, and Internalisation, i.e. personal knowledge development outcomes.

Taking an action research approach, this study explores the experiences of three intakes of undergraduate students who worked in a cohort-based learning environment where team work and classroom participation was expected. This educational setting required students from diverse backgrounds to work closely together on campus during the intense one-year program. To facilitate in the development of a face-to-face learning community, where individual differences could be celebrated and problems could be solved in an open, trusting environment, an online bridging course was developed. Aimed at decreasing the incidence of minority group marginalization and reduce feelings of isolation, the bridging course provided activities directed towards encouraging students to begin to develop an inclusive learning community prior to their arrival on campus. Exploring how online transitional activities had contributed to the development of a face-to-face learning community, as well as perceived disadvantages to that model, key stakeholders' perceptions were obtained through focus groups, interviews, and surveys. Findings include: (a) an enhanced understanding of the ways in which an online course can be used to aid in the development of a learning community for oncampus students; (b) a heightened awareness of challenges faced by those working in a learning community; (c) a systematic approach to the development of learning communities. This research suggests that an online bridging course can be an effective way for on-campus students to start developing a learning community.

The quality of the student learning experience in an online learning course has raised many debates in educational studies. Evidence found in current literature indicates that individualised learning and interactive learning do contribute to the student learning experience in online learning courses. However, there is little evidence of any major studies that have tried to explore the impact of both individualised learning and interactive learning on the students' experience. Drawing on the constructivist "student-centred" learning perspective, this study aims to match instructional methods to the students' individual learning pace, learning styles and individualised course content in a technology- enhanced learning environment. The study was carried out in China with fourth-year undergraduate computing science students enrolled on a Cisco CCNA course. The study was carried out using a mixed methods research approach. Qualitative data were analysed using content analysis and quantitative data were analysed using SPSS. The findings of this study suggest that students taking an online course in which the contents/materials are individualised (based on: learning style, learning pace and prior knowledge structure), and who are supported with relevant interactions and learning objects technology, have an improved quality of learning and a better learning experience than the normal 'one-size-fits-all text/graphic based format' online course or the online course with only individualised features or interaction tools. Results from this study found significant statistical difference in both the level of students' achievement and learning experience. This study confirmed that synergies could be formed by combining individualised learning and interactive learning within an online learning environment. It also demonstrated that students with different learning styles interact more effectively in online learning courses. An interaction model has been designed to guide the design and implementation of effective learning in online situations through a diverse range of interactions. The findings of this study may be impacted upon by the cultural norm of 'strict compliance to rules and regulations' within the Chinese educational system. The study proposes educational principles to support the transferability of individualised and interactive learning to other cultures and disciplines.

Many classification algorithms are designed on the assumption that the population of interest is stationary, i.e. it does not change over time. However, there are many real-world problems where this assumption is not appropriate. In this thesis, we develop a classifier for non-stationary populations which is based on a multiple logistic model for the conditional class probabilities and incorporates a linear combination of the outputs of a number of pre-determined component classifiers. The final classifier is able to adjust to changes in the population by sequential updating of the coefficients of the linear combination, which are the parameters of the model. The model we use is motivated by the relatively good classification performance which has been achieved by classification rules based on combining classifier outputs. However, in some cases such classifiers can also perform relatively poorly, and in general the mechanisms behind such results are little understood. For the model we propose, which is a generalisation of several existing models for stationary classification problems, we show there exists a simple relationship between the component classifiers which are used, the sign of the parameters and the decision boundaries of the final classifier. This relationship can be used to guide the choice of component classifiers, and helps with understanding the conditions necessary for the classifier to perform well. We compare several "on-line" algorithms for implementing the classification model, where the classifier is updated as new labelled observations become available. The predictive approach to classification is adopted, so each algorithm is based on updating the posterior distribution of the parameters as new information is received. Specifically, we compare a method which assumes the posterior distribution is Gaussian, a more general method developed for the class of Dynamic Generalised Linear Models, and a method based on a sequential Monte Carlo approximation of the posterior. The relationship between the model used for parameter evolution, the bias of the parameter estimates and the error of the classifier is explored.

Advances in technology such as increased Internet access and digital multimedia provide opportunities for developing innovative teaching and learning materials. Learning theory supports the use of computer-based learning materials in providing flexible access to self-study materials, which can be tailored to the needs of specific courses and may appeal to students with a wide range of learning styles. There is some evidence to support the use of these technologies in facilitating learning, but evaluations apply only to specific learning materials in the environment in which they were tested. Students of Health Sciences need access to clinically-relevant self-study materials that allow for feedback, and which facilitate understanding and application of knowledge. Identification of potential areas where computer-based resources can be used to support students' self-study has informed the development of three differently-focussed computer-based self-study packages. The Movement Analysis, Manual Therapy and Stroke packages were developed using the assessment software "Questionmark Perception" and linked video clips. These packages were integrated into the modules they were designed to support and evaluated by the different groups of Health Science students taking these modules. The evaluation comprised: a) a questionnaire about students' attitudes, and b) the use of tracking data from the Manual Therapy and Stroke packages to monitor students' activity with the packages. Students exhibited positive attitudes towards all the packages, the Stroke package format proving the most popular. Although the MSc (pre-registration) physiotherapy student group found the Manual Therapy and Stroke packages beneficial, they were significantly less positive towards different features of these packages. Otherwise, no significant differences were found between different course groups, ages and genders of students using these packages. Analysis of the tracking data revealed significant positive correlations between the amount of times students accessed the packages, and their improvement in self-study scores for both the Manual Therapy and Stroke packages. The time spent using the packages and students' self-study scores for the Manual Therapy package were also significantly positively correlated. Correlations between student access and test score were not significant. In conclusion, these packages provide appropriate and effective self-study materials for the groups of students studied. Development and updating of these and similar packages should be continued. Further research is required to evaluate their effects with larger samples of students, and to further investigate the relationship between package use and test scores.

Motivation, belonging, and inclusion are all critical factors for student success but can be difficult to support in asynchronous online courses. Active learning and required group work have been shown to increase student motivation in in-person and synchronous online courses, but little is known about their impact in online asynchronous settings. This dissertation aimed to 1) evaluate the effect of active learning on student motivation in an online asynchronous setting and 2) evaluate the impact of assigned group work on student motivation and perceptions of belonging and inclusion within the context of an online, asynchronous physiology laboratory course. It was found that students assigned to group work felt a greater sense of belonging and had higher competence-related beliefs and lower effort and psychological costs associated with the course compared to students not assigned to group work. Inductive coding of open-ended survey questions revealed that students assigned to group work perceived peer interactions as the most inclusive aspect of the course, while students not assigned to groups perceived instructor interactions as the most inclusive aspect.

Online learning provides secondary students with the flexibility to meet learning goals at a time, place, and pace that meets their needs. In order to be successful in online courses, students must exhibit strong levels of self-regulated learning (SRL), including time management, goal setting, and resilience. Understanding the SRL behaviors of secondary online students can help course designers, instructors, and administrators design effective learning environments and provide targeted support to help students be successful in online learning environments. This three-manuscript dissertation analyzes the course pacing behaviors of secondary students enrolled in online courses to attain insight on their self-regulated behaviors. As a proxy for understanding online self-regulated behaviors, temporal variables were examined including the average length of an online study session, the amount of time between study sessions, the average number of study session sand the overall number of study sessions for each participant. The first study investigated the relationships between student demographics and temporal behaviors in relation to their effect on the depth of student understanding on the course midterm exam. The second study explores trends in online temporal behaviors, including the consistency and frequency of engagement in the course, and how these behaviors change over time in relation to student demographics. The final article utilizes student demographics and temporal behaviors to study their effect on academic achievement, as measured by their performance on the Advanced Placement exam. Findings from these studies indicate that online pacing behavior is related to student demographics and previous academic experience while also providing insight into how these variables affect achievement. By understanding the temporal behaviors of online secondary students, personalized support can be provided to strengthen student time management and engagement to promote academic achievement.

This research study explicates the underrepresentation of Black students in public school instrumental music programs through a critical race perspective, focusing on socioeconomic and epistemological barriers perpetuated by public policy and school music curricula. Such barriers have encouraged some Black musicians to seek agency and satisfy their musical interests in spaces outside of the classroom, particularly in the church and community. Considering that the theory of disruptive innovation purports the potential to increase access and disrupt both socioeconomic and epistemological barriers through the use of technology, this exploratory research study sought to investigate whether Black instrumental musicians use technology in order to disrupt the socioeconomic and epistemological barriers unveiled by a critical race perspective. By employing qualitative research methods, participants’ personal experiences were synthesized into a thematic analysis which ultimately support the potential of technology to increase access, revealing that participants successfully disrupted socioeconomic and epistemological barriers through the use of asynchronous online lessons.

The field of online language education is experiencing rapid growth, emphasizing the need to understand factors that influence students' communication behaviors in online learning environments. This research study examines the relationships between need satisfaction, willingness to communicate (WTC), quantity of communication(i.e., frequency of communication), and quality of communication (i.e., language performance) in asynchronous and synchronous learning modes. Using Experience Sampling Methodology, data was collected from high school students enrolled in an online language course. Weekly surveys were used to capture participants' situational need satisfaction, WTC, and quantity of communication. Quality of communication was assessed through weekly writing assignments and synchronous speaking performance. Findings from multiple group path analyses revealed that students' need satisfaction for competence, and relatedness were significantly related to their WTC in both asynchronous and synchronous learning modes. The study identified differences in relationship patterns in asynchronous and synchronous learning modes, highlighting the influence of specific contextual factors on communication behaviors.Additionally, the study employed cross-lagged analyses to explore the temporal effects between need satisfaction and WTC, and between WTC and communication behaviors. The findings revealed the associations between students’ prior learning experiences, students' perceptions, and subsequent engagements over time. The study explored the specificity of relationships within and across learning modes and content units, providing insights into contextual factors that are associated with students' communication behaviors. By examining the differences in relationships across various modes and considering temporal dynamics within specific contexts, this research enhances our understanding of factors contributing to supportive online environments and positive communication behaviors.

The purpose of this quantitative, causal-comparative study is to investigate the current differences between online and face-to-face student attitudes toward mathematics and computer-based learning at the high school level. Because instruction and technology use have been influenced by the Covid-19 pandemic, it is important to assess student attitudes toward mathematics and computer-based learning in both traditional face-to-face and online settings. This study was conducted with 70 face-to-face students and 67 online high school students in a single school district in North Carolina. The Galbraith-Haines Mathematics-Computer Attitude Scales were used as the data collection instrument measuring student confidence toward mathematics, mathematics motivation, computer confidence, and computer-mathematics interaction. A secure Google form was used for data collection in the spring of 2023. A one-way MANOVA was used to determine if there was a difference in attitudes between the online and face-to-face participants in the dependent variables. The result of the MANOVA was significant, where F(4, 127) = 10.448, p < .001, Pillai’s Trace = .248, and partial η^2 = 0.248, suggesting there are significant differences on the dependent variables by setting type for high school mathematics students in online and face-to-face settings. Results indicated a higher confidence in mathematics held by face-to-face students, higher mathematics motivation held by online students, and higher computer-mathematics interaction held by online students. No significant difference was found between online and face-to-face students in the area of computer confidence. Recommendations for further studies include a larger sample size, a comparison of technology uses, and a qualitative study.

The purpose of this non-experimental causal-comparative study was to determine whether there is a statistically significant difference in the academic performance of high school students with and without disabilities who received math instructions in face-to-face and online educational settings during the 2020-2021 school year. During that year, educational establishments worldwide transitioned from traditional face-to-face to online delivery mode, complying with the social distancing requirements due to the COVID-19 pandemics. The current study employed a convenience sample that consisted of 588 high school students from Georgia. Participants took the Georgia Milestones End-of-Course Test in Algebra I in the spring of 2021 after receiving math instructions in the online or face-to-face settings. The researcher used this test as the instrument and compared the participants’ scores. A two-way analysis of variance was used to examine the differences among six groups of students based on their disability status and the number of semesters taken online. The findings revealed that students with disabilities exhibited lower academic performance in math compared to their general education peers. Additionally, the study suggested that the transition to online learning during the COVID-19 pandemic had a negative impact on learning outcomes for all participants. However, the study did not find a significant interaction between students’ disability status and the number of online semesters in relation to their academic performance. The limitations of the study included the specific population and quasi-experimental design. Recommendations for future research addressed the factors that may affect students’ learning outcomes in online and face-to-face settings.

This transcendental phenomenological study had the objective of examining the experience of faculty subject matter experts in higher education as they collaborated with instructional designers to develop online learning courses at a college in the northeast United States. The theory guiding this study was Bandura’s theory of self-efficacy. The central research question was: What are the SME reflections on their previous pedagogical and instructional skills, and what growth, if any, can be identified after the course design process? Additional questions examined the faculty's perspective on their past and present pedagogical knowledge. The study took place at a four-year private college in the northeast. The sampling included 12 adjunct faculty members who have completed at least one online course design collaboration with an instructional designer. Data collection included one-on-one interviews, observations of course design documents, and faculty journal reflections. The researcher examined themes regarding the faculty perspective on what knowledge they acquired from the course design process and in what areas they determined professional growth. Five major themes emerged from the data analysis: (a) excited but cautious, (b) streamlined process, (c) relationship is critical, and (d) a new adventure. The examination encompassed the interpretation of the study's findings, an exploration of its limitations, and the formulation of recommendations for future research.