Search

Treatment adherence is one of the milestones in the care of hypertensive patients, with new information and communication technologies as potential educational tools. This study aimed to evaluate the add-on effect of a digital cartoon educative video on the therapeutic observance of patients followed up in the General Hospital Yaoundé compared to standard of care. We conducted a randomized simple blind clinical trial at the cardiology unit of the Yaoundé General Hospital over a 6-month period from 1st March to 30th August 2022. We enrolled 110 patients and randomized them in blocs of 4 creating two groups of 57 and 53, respectively, without (group 1) and with (group 2) intervention. Preintervention treatment adherence was assessed using the Morisky Medication Adherence Scale (MMAS). In the standard group (G1), we provided standard paper-based clinical counselling, including oral advice, and in the intervention group (G2), we did the same and added a digital cartoon video containing exactly the same message as images and audio. The primary outcome was medication adherence after three months. The mean age was 56.65 ± 10.98 years in group 1 (paper) and 56.42 ± 10.46 years in group 2 (paper + video), without any significant difference. The two groups were similar regarding the proportion of females (36.8% in G1 and 49.3% in G2) and educational levels. According to the Morisky medication adherence scale, before the intervention, the proportions of patients with good, medium and low treatment adherence in groups 1 and 2 were 7%, 25.6%, 67.4%, and 5.1%, 43.6%, 51.3%, respectively, without any significant difference. After interventions, the proportion of patients presenting a good observance moved from 7 to 11% in group 1 (paper) and 5.1 to 20% in group 2 (paper + video). The intragroup variation in treatment adherence in the intervention group (before-after) tended to be significant, with a p-value = 0.0572, while this p-value was 0.712 in the standard group. Our results provide insight into how digital cartoon videos can help to have an add-on effect on the treatment adherence of hypertensive patients, with clinical significance. [ABSTRACT FROM AUTHOR]

The diversity and advance of information, communication, and analytical technologies and their increasing adoption to assist instruction and learning give rise to various technology-driven conferences (e.g., artificial intelligence in education) in educational technology. Previous reviews on educational technology commonly focused on journal articles while seldom including mainstream conference papers which also contribute to an important part of scientific output in computer science and emerging disciplines like educational technology and are equally and even more important than articles in knowledge transmission. Hence, conference papers should also be included in bibliometric studies to produce a complete and precise picture of scientific production concerning educational technology. This study, therefore, uses bibliometrics and topic modeling to analyze papers from mainstream conferences, including Artificial Intelligence in Education, Learning Analytics and Knowledge, Educational Data Mining, Intelligent Tutoring System, and Learning at Scale, focusing on contributors, collaborations, and particularly research topics and topic evolutions to inform relevant stakeholders about educational technology's development and its future. Results indicate promising areas like affective computing and behavior mining for adaptive instruction, recommender systems in personalized learning recommendations, eye-tracking for cognitive process diagnosis, videos for feedback provision, and natural language processing in discourse analysis and language education. [ABSTRACT FROM AUTHOR]

External audit is undergoing rapid changes where more and more routine tasks are automated with analytics and artificial intelligence (AI) instruments. The paper addresses a research problem of mapping data analytics to audit tasks and develops a framework aligning audit phases and AI and using data analytics in teaching audit with AI. The paper contributes to the literature on using data analytics with AI in knowledge specific areas and particularly critical for emerging audit analytics, which is data analytics in external financial audit application. The paper employs the process model methodology (Wynn and Clarkson, Research in Engineering Design 29:161–202, 2018) and the hybrid approach of curriculum development (Dzuranin et al., Journal of Accounting Education 43:24–39, 2018). The framework is extended further by inclusion of knowledge areas and skills recommendations for each identified stage. This inclusion is linked to the peak accounting body guidelines to ensure compliance with course certification and future job prospects. The developed framework is implemented using audit management platform MindBridge AI. The developed teaching and learning materials show implementation of the framework on the practical level. The developed framework was evaluated in a focus group with accounting academics and industry professionals. Its implementation was evaluated in a series of workshops and a survey with participants. [ABSTRACT FROM AUTHOR]

Online learning has significantly expanded along with the spread of the coronavirus disease (COVID-19). Personalization becomes an essential component of learning systems due to students' different learning styles and abilities. Recommending materials that meet the needs and are tailored to learners' styles and abilities is necessary to ensure a personalized learning system. The study conducted a systematic literature review (SLR) of papers on recommendation systems for e-learning in the K12 setting published between 2017 and 2021 and aims to identify the most important component of a personalized recommender system for school students' e-learning. Recommendations for later studies were proposed based on the identified components, namely a personalized conceptual framework for providing materials to school students. The proposed framework comprised four stages: student profiling, material collection, material filtering, and validation. [ABSTRACT FROM AUTHOR]

The present study aimed to present how eye-tracking is employed in special education. While presenting the use of eye-tracking technology, the research considered some eye-tracking-related aspects, such as its potential to facilitate the education of children with special needs, investigation of disabilities through eye-tracking technology, and the relationship between learning outcomes and eye-tracking measurements in studies including children with special needs. Within specified criteria, this systematic review was carried out using famous electronic databases, such as Web of Science, Scopus, Science Direct, Education Source, Education Resources Information Center (ERIC), and EBSCOhost. Accordingly, 48 papers reviewed demonstrated an increasing trend in the use of eye-tracking technology in special education research. The age range of the target group recruited in previous research was often between 6 and 11 years, and reading and word learning were the most studied learning outcomes. Moreover, dyslexia and autism spectrum disorder (ASD) were commonly investigated by children's eye movements, particularly fixation duration and fixation count. This study also revealed that eye-tracking technology is helpful in exploring reading, word learning, mathematics skills, social communication, language development, motor learning, eyesight improvement, and route learning in special education. Furthermore, it is pretty suitable and effective to utilize eye-tracking technology as assistive technology (AT) to improve the learning environments of children with special needs. [ABSTRACT FROM AUTHOR]

This paper proposes the BP-CM teaching model to solve the problems of lagging classroom feedback, poor learning initiative of students and students rapidly forgetting what they have learned in Internet of Things (IoT) hardware technology courses. This BP-CM(BOPPPS, PAD, cyclic memory, memory system) teaching model is based on BOPPPS(Bridge in, Objective, Pre-assessment, Participatory learning, Post-assessment, and Summary), PAD(Presentation, Assimilation, and Discussion), and the memory system model. This paper compares the BP-CM teaching model with the traditional teaching model by having research participants teach and learn separately in each teaching model. Taking the Microcontroller Unit (MCU) course as an example, this paper introduces each link of the teaching design of this model. It also explains the design method and intention of each link. Finally, the practical results indicate that the BP-CM teaching model proposed in this article positively impacts students' learning initiative and memory. In addition, teachers can obtain timely feedback using the BP-CM model, and the model significantly improves students' knowledge and ability levels. It enhances the teaching quality of IoT hardware technology courses and is conducive to cultivating students' sustainable learning abilities. This research not only promotes education and teaching reform but also provides a reference case. [ABSTRACT FROM AUTHOR]

Score interchangeability of Computerized Fixed-Length Linear Testing (henceforth CFLT) and Paper-and-Pencil-Based Testing (henceforth PPBT) has become a controversial issue over the last decade when technology has meaningfully restructured methods of the educational assessment. Given this controversy, various testing guidelines published on computerized testing may be used to investigate the interchangeability of CFLT and PPBT mean scores to corroborate if test takers' testing performance is influenced by the effects of testing administration mode; specifically, if validity and reliability of two versions of the same test are affected. This research was conducted to probe not only score interchangeability across testing modes but also to explore the role of age and gender stereotypes, item review, ICT literacy and attitudes towards computer use as moderator variables in test takers' reading achievement in CFLT. Fifty-eight EFL learners homogeneous in both general English and reading skills assigned into one testing group participated in this study. Three different versions of TOEFL reading comprehension test, Computer Attitude Scale (CAS), and ICT literacy Scale of TOEFL Examinees were used in this crossover quasi-controlled empirical study with a common-person and pretest–posttest design to collect data. The findings demonstrated that although the reading scores of test takers were interchangeable in both CFLT and PPBT versions regarding testing administration modes, they were different regarding item review. Furthermore, no significant interaction was found between age, gender, and ICT literacy and CFLT performance. However, attitudes towards the use of computer led to a significant change in testing achievement on CFLT. [ABSTRACT FROM AUTHOR]

Collaborative design approaches have been increasingly adopted in the design of learning technologies since they contribute to develop pedagogically inclusive and appropriate learning designs. Despite the positive reception of collaborative design strategies in technology-enhanced learning, little attention has been dedicated to analyzing the challenges faced in design processes using a collaborative approach. In this paper, we disclose the collaborative design of a chatbot for self-regulated learning in higher education using an action research approach. We analyze the design process of EDUguia chatbot, which includes diverse evidence from questionnaires and workshops with students and lecturers, as well as intermediary design objects. Based on the qualitative analysis, we identify several challenges that are transversal to the co-design work, as well as specific to the design phases. We critically reflect on the strategies deployed to overcome these challenges and how they relate to decision-making processes, highlighting the need to make stakeholders' tacit knowledge explicit, cultivate trust-building and support democratic decision-making in technology design processes. We believe that the recommendations we present in this paper contribute to developing best practices in the collaborative design of chatbots for the self-regulation of learning, as well as learning technology in general. [ABSTRACT FROM AUTHOR]

Educational data mining is an emerging interdisciplinary research area involving both education and informatics. It has become an imperative research area due to many advantages that educational institutions can achieve. Along these lines, various data mining techniques have been used to improve learning outcomes by exploring large-scale data that come from educational settings. One of the main problems is predicting the future achievements of students before taking final exams, so we can proactively help students achieve better performance and prevent dropouts. Therefore, many efforts have been made to solve the problem of student performance prediction in the context of educational data mining. In this paper, we provide readers with a comprehensive understanding of student performance prediction and compare approximately 260 studies in the last 20 years with respect to i) major factors highly affecting student performance prediction, ii) kinds of data mining techniques including prediction and feature selection algorithms, and iii) frequently used data mining tools. The findings of the comprehensive analysis show that ANN and Random Forest are mostly used data mining algorithms, while WEKA is found as a trending tool for students' performance prediction. Students' academic records and demographic factors are the best attributes to predict performance. The study proves that irrelevant features in the dataset reduce the prediction results and increase model processing time. Therefore, almost half of the studies used feature selection techniques before building prediction models. This study attempts to provide useful and valuable information to researchers interested in advancing educational data mining. The study directs future researchers to achieve highly accurate prediction results in different scenarios using different available inputs or techniques. The study also helps institutions apply data mining techniques to predict and improve student outcomes by providing additional assistance on time. [ABSTRACT FROM AUTHOR]

A discussion forum is an indispensable part of a massive open online course (MOOC) environment as it enables knowledge construction through learner-to-learner interaction such as discussion of solutions to assigned problems among learners. In this paper, a machine prediction model is built based on the data from the MOOC forum and the depth of discussion of solutions to assigned problems on the topic among students was analyzed. The data for this study was obtained from Modern educational technology course through Selenium with Python. The course has been offered to a total of 11,184 students from China seven times since February, 2016. The proposed model includes the formula of the depth of problem-solving discussion in MOOC forum and its prediction probability. The efficiency of the prediction model and the most important factor of the depth of problem-solving discussion in MOOC are explained in the paper. Based on the results, useful suggestions for effective teaching in MOOC forums are provided in the article. [ABSTRACT FROM AUTHOR]

Different instructional strategies have been drawn to assist elementary school students in improving computational thinking (CT) skills and student engagement (SE) in unplugged programming activities. This paper aimed to explore how the interactive strategies of unplugged programming affect CT skills and SE. The study was conducted based on a quasi-experimental research method. The sample was composed of 104 sixth-grade students from northern China. The students in the experimental group learned with interactive unplugged programming, whereas those in the control group learned with non-interactive unplugged programming. Analysis of Covariance statistics and Partial Least Squares Structural Equation Modeling were adopted for data analysis. Results showed that the performance of the experimental group in CT skills and SE was considerably better than that of the control group. Moreover, the predictive relationships were more complex between CT skills and SE in the experimental group. In general, these findings confirmed the teaching value of interactive unplugged programming, and further emphasized the important role of students' CT skills in programming engagement. Therefore, through the application of interaction in instruction design, each student can be assigned a positive role to create a programming classroom that is more conducive to students. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the guest editors talk about the topics discussed in the special section of the issue including the need to balance computer science (CS) and information and communication technologies (ICT), overview of CS curriculum development, and use of ICT to support teaching and learning.

Learning Design (LD) research accounts for several design support tools, or LD tools, employing representations for learning designs to facilitate the "teachers as designers" thinking while preparing learning experiences. In contrast to existing studies having followed mainly a specialist/researcher (as opposed to a teacher) perspective, our quest to develop an LD tool follows a Design-Based Research (DBR) approach involving practitioners. Specifically, in this paper, we attempt to give voice to teachers as designers and investigate how they prefer having their learning designs represented by LD tools. Aiming to create a principled account of how to represent learning designs in an LD tool, we first conducted an integrative literature review to formulate a representational framework that drove our research. Subsequently, we addressed the following LD representational dimensions: (i) format, (ii) organisation, (iii) guidance and support, and (iv) contextualisation. We are reporting on a case study conducted with 16 participants in a teacher education context. Although previous research typically reported findings based on a single LD tool's evaluation over a short period, we have opted for eliciting feedback based on a rich LD experience. To this end, we acquainted participants in LD projects with two LD tools (Learning Designer and WebCollage) during an academic semester. Furthermore, we followed a mixed-method explanatory sequential design applied through a survey questionnaire and semi-structured interviews to achieve a more profound consideration of the teachers' preferences for LD representations. Our findings indicate that the teachers strongly endorse an LD tool supporting a visual format and a global organisation in the form of a table that provides a global overview of a learning design while focusing on its specific elements. Teachers seem to prefer an LD tool that balances providing guidance and flexibility, as they opt for (i) a non-restrictive taxonomy for articulating learning objectives, (ii) some form of standardisation for formatting learning units, along with allowing free formation, (iii) a flexible pedagogical framework for modelling the learning activities' pedagogy so that it can be adjusted to particular designers' needs, and (iv) a typology of technologies that can be utilised or not. In addition, they seemed to favour an LD tool supporting high contextualisation, as they prefer to describe contextual details for a learning design's units and activities. These findings constitute design principles for our ongoing DBR and may stimulate momentum for researchers developing LD tools. [ABSTRACT FROM AUTHOR]

The replacement of existing technology or the introduction of novel technology into the day-to-day routines of higher education institutions is not a trivial task. Currently, many higher education institutions are faced with the challenge of replacing existing procedures for administering written exams with e-exams. To guide this process, this paper proposes the novel technology-based exams acceptance model (TEAM) and empirically evaluates its model structure and usefulness from the perspective of higher education teachers. The model can be used to guide the transition from paper-based exams to e-exams and the implementation of innovative (e.g., adaptive) e-exam formats. The model includes perceived usefulness, computer self-efficacy, computer anxiety, prior experience, facilitating conditions, and subjective norm as predictors of the behavioral intention to use e-exams. To test the model empirically, the responses of 992 teachers at 63 German universities to a standardized online questionnaire were analyzed using structural equation modeling. The model fit was acceptable. With 77% (conventional e-exams) and 82% (adaptive e-exams), a large proportion of the variance of the intention to use these types of exams was explained. With TEAM, a highly predictive model for explaining the behavioral intention to use e-exams is now available. It offers a theoretical basis that can be used for the successful implementation of e-exams in higher education. [ABSTRACT FROM AUTHOR]

The importance of providing mechanisms and tools that effectively support the transition from implicit to explicit representations of Learning Design has been emphasised by previous research in the field of Technology-Enhanced Learning (TEL). In addition, the benefits of Game-based learning approaches have been long documented in the educational research literature. The paper presents the design, implementation and evaluation of a card game that aims to support the design process of TEL activities in higher education. The game was tested by a group of 36 students and tutors (n = 36) in higher education during an interactive workshop. Feedback was asked by the participants using an anonymous survey. The results reveal that the participants a) are satisfied with the game process, b) appreciate the groupwork and interaction taking place, and c) believe that they used their communication and collaboration skills. The paper includes the description of the outputs of a group (i.e., the cards selected for their TEL scenario and their actual TEL scenario) to exemplify that it is possible to use the game in order to elicit or diagnose existing LD knowledge from the game participants. The paper concludes on the usefulness of the approach suggested, limitations, and plans for future work. [ABSTRACT FROM AUTHOR]

Educational technology is a discipline that has a lot of roles to play in the global education system yet, its services had been neglected over the years in Nigeria. The new global reality that was occasioned by the upsurge of COVID-19 has made educational technology a very consequential discipline with conspicuous roles to play in the face of such a global pandemic. COVID-19 has halted many human activities across the globe. Its effect in the education system has resulted to re-adjustment in the school calendar, prolonged graduation dates, and reduced research output. To combat this, many education systems now adopt the services of educational technology thereby changing the old norm. But for this new norm to be sustainable, this paper argues that the education system must show a pragmatic attitude towards the adoption of such innovation rather than a conservative attitude. Therefore, using the diffusion theory of innovation, this paper argues that necessity called for compulsory adoption of innovation in the Nigerian education system. This new opportunity, however, looks bleak as many educational practitioners lack the required skills and attitude to adopt the innovation. It, therefore, concludes that educational practitioners need in-service training to be part of these changes. The government is suggested to apply a systematic approach in procuring and installing ICT facilities that will enhance the diffusion of this innovation into the school system. [ABSTRACT FROM AUTHOR]

Automated writing evaluation (AWE) systems are developed based on interdisciplinary research and technological advances such as natural language processing, computer sciences, and latent semantic analysis. Despite a steady increase in research publications in this area, the results of AWE investigations are often mixed, and their validity may be questionable. To yield a deeper understanding of the validity of AWE systems, we conducted a systematic review of the empirical AWE research. Using Scopus, we identified 105 published papers on AWE scoring systems and coded them within an argument-based validation framework. The major findings are: (i) AWE scoring research had a rising trend, but was heterogeneous in terms of the language environments, ecological settings, and educational level; (ii) a disproportionate number of studies were carried out on each validity inference, with the evaluation inference receiving the most research attention, and the domain description inference being the neglected one, and (iii) most studies adopted quantitative methods and yielded positive results that backed each inference, while some studies also presented counterevidence. Lack of research on the domain description (i.e., the correspondence between the AWE systems and real-life writing tasks) combined with the heterogeneous contexts indicated that construct representation in the AWE scoring field needs extensive investigation. Implications and directions for future research are also discussed. [ABSTRACT FROM AUTHOR]

Interdisciplinary team communication in eHealth development is challenging because all disciplines have unique, intrinsic discursive practices, theories and artefacts. Due to these factors, members of interdisciplinary teams can experience problems in communication and collaboration. Through a centered focus, members can benefit individually, inspire one another, and ultimately reach a timely delivery of their common pedagogical goal(s). Using the lens of dialogism, this paper aims to identify the conceptual considerations that arose during the development of a Massive Open Online Course (MOOC) for higher education in eHealth. Methods included auto-ethnography and interdisciplinary dialogue supported by literacy artefacts, including visual material. Results yielded a visual tool for meta-assessment of team communication, and an organizing principle for topics in the MOOC. A major implication is that especially for eHealth, scientific communicative competence of experts—while establishing a common understanding—can lead to a unique and meaningful delivery of high pedagogical quality. [ABSTRACT FROM AUTHOR]

Due to the inherently dangerous environment in the maritime industry, it is an essential aspect for the human resources in the industry to have a high level of knowledge, skill and competence. Therefore, maritime education and training needs to be structured as a unique instructional design model that will ensure the acquisition of the required knowledge, skills, and competencies at the highest level. In this paper, we develop a new approach using an axiomatic design methodology extended with fuzzy set theory to define the suitable instructional design model for maritime education and training. Accordingly, we aimed to establish a decision support system for instructional designers at an institutional level and instructors at the individual level who focus on instructional design, development, and processes. The demonstration of the proposed approach is conducted for basic offshore safety induction and emergency training which is one of the compulsory training courses for people who already work or will work on offshore facilities. [ABSTRACT FROM AUTHOR]

Educational communities have expanded 3D printing in education, emphasizing the educational value of "creation" to develop the competencies required in the future. This study was conducted for the purpose of identifying the effect size by synthesizing prior studies on the effect of 3D printing in education. To achieve the goal, 26 research papers on 3D printing in education conducted in South Korea from 2014 to 2021 were selected and meta-analysis was performed. The results of meta-analysis are as follows. First, the overall effect size of 3D printing in education was 0.759, which was found to be a medium effect size. Second, the effect sizes for each categorical variable are as follows: both the affective domain and the cognitive domain showed medium effect sizes for the learning effects. Middle school showed a large effect size, and elementary school and high school had a medium effect size. Gifted students had a large effect size, and general students had a medium effect size. In terms of the concentrated subjects, mathematics showed a large effect size and science and technology showed a medium effect size. Single subject showed a large effect size and convergence education had a medium effect size. Both offline classes and blended classes showed increased effect sizes. Both the team activity and the individual activity showed a median effect size. The out-of-school program showed a large effect size, and the school program showed a medium effect size. 3D pens showed a large effect size, and 3D printers showed medium effect size. In terms of the modeling type, unstructured modeling showed a large effect size, as did semi-structured modeling, while semi-structured modeling showed a medium effect size. This study has implications for instructional design that can increase the effect of 3D printing in education. [ABSTRACT FROM AUTHOR]

Conflicts play an important role to improve group learning effectiveness; they can be decreased, increased, or ignored. Given the sequence of messages of a collaborative group, we are interested in recognizing conflicts (detecting whether a conflict exists or not). This is not an easy task because of different types of natural language ambiguities. A conversation can be represented as a conversation graph; i.e., a direct multidigraph where the nodes are users, and an edge means a message. The approach proposed in this paper focuses on the emotional interactions of group members. Hence, to detect conflicts it analyzes emotions involved in the cycles of the graph. This strategy has the advantages of considering the sentiment of a sequence of messages to take a better decision and analyzing interactions with two or more participants. The proposed approach has been tested in collaborative learning tasks, achieving an F1 score of 92.6%, and a 90.1% recall score for conflicting situations. This approach can help teachers and students to improve the learning process. [ABSTRACT FROM AUTHOR]

The freshman student's perspective on the activities performed in a data center by the network analyst is complex and intricate. These activities include the configuration of equipment and the connection between network devices. There are several issues with these activities that demand technical knowledge. Questions such as: "what does this equipment do?"; "How is it connected to another?"; "How is it configured?" can be complicated for beginner students. Moreover, these technical questions are also associated with scalability, availability, security, portability, accounting, and costs. These resources require technical knowledge and also how to aggregate them into a network solution. We applied an abstraction set to mitigate these issues for first-year students and created the Network Analyst Board Game. This board game introduces students to the computer network field geared toward Data Center activities. The objective of this paper is to report this game. The students obtained essential theoretical and practical knowledge regarding computer networks after playing. A quasi-experiment was conducted with a set of students from the computing courses. After these experiments, more interactivity was noted among the students, resulting from the game mechanics applied. Therefore, in addition to increasing their interest in the area, the students elaborated more complex questions. The professors found that, after playing, the students presented more pertinent doubts during classes. [ABSTRACT FROM AUTHOR]

This paper applies Information and Communication Technologies (ICT) as well as data analysis to gain a better understanding of the existing perception on the education system. 45,278 tweets were downloaded and processed. Using a lexicon-based approach, examining the most frequently used words, and estimating similarities between terms, we detected that a predominantly negative perception of the education system exists in most of the analysed countries. A positive perception is identified in certain low-income nations. Men exhibit a more positive sentiment than women as well as a higher subjectivity in some countries. The countries that exhibit the most positive perceptions India, Canada, Pakistan, Australia, South Africa and Kenya are also those that manifest the highest subjectivity. [ABSTRACT FROM AUTHOR]

The main drive for this study is to look into potential predictors of educational achievement using OECD's original Pisa 2018 dataset. This paper explores (i) access to ICT, (ii) physical characteristics of learning environment at school, (iii) quality of teaching staff and educational material, (iv) student characteristics and learning climate, and (v) political and economic structure of the country as potential true predictors of academic achievement. Our sample covers 41 countries and data used in our analysis are collected from 282,461 students distributed in 9,317 schools worldwide. Multiple linear regressions are developed and analyzed using stepwise estimation techniques. The results indicate that (i) availability of internet connection and enjoyable pastime activity at home have positive impacts on student's success, (ii) a strong correlation exists between high test scores and student characteristics & learning climate, i.e. students' sense of belonging at school, students' fear of failure and disciplinary climate, (iii) there is a negative relationship between academic performance and teacher enthusiasm & support, (iv) student success is negatively correlated with income level and political and economic freedoms but positively associated with economic competitiveness of a country, and (v) the students in lightly populated classes are more successful than those in overloaded ones and inadequate or poor educational material deteriorates educational outcomes. [ABSTRACT FROM AUTHOR]

Educational technologies have captured the attention of researchers, policy makers, and parents. Each year, considerable effort and money are invested into new technologies, hoping to find the next effective learning tool. However, technology changes rapidly and little attention is paid to the changes after they occur. This paper provides an overall picture of the changing trends in educational technology by analyzing the Horizon Reports' predictions of the most influential educational technologies from 2011 to 2021, identifying larger trends across these yearly predictions, and by using bibliometric analysis to evaluate the accuracy of the identified trends. The results suggest that mobile and analytics technologies trended consistently across the period, there was a trend towards maker technologies and games in the early part of the decade, and emerging technologies (e.g., VR, AI) are predicted to trend in the future. Overall, the specific technologies focused on by the HRs' predictions and by educational researchers' publications seem to coincide with the availability of consumer grade technologies, suggesting that the marketplace and technology industry is driving trends (cf., pedagogy or theory). [ABSTRACT FROM AUTHOR]

E-Assessment, which is a key element in the instructional design process, plays a major role in supporting and enhancing learning. However, the current e-assessment design does not achieve the desired pedagogical objectives in the e-learning environments. In this paper, we propose a hybrid pedagogical framework for e-learning environments, that includes a set of principles for competencies assessment design based on the Competency-based Approach (CBA) and Objective-based Approach (OBA). In addition, we present an authoring tool that illustrates the assessment design based on this proposed framework. This tool aims to support and assist teachers to create assessment activities suited to competency levels in a guided, controlled, and easy way. One of the main messages of this paper is that explicit use of pedagogical approaches allows the successful guidance of the teachers and effective e-assessment design. [ABSTRACT FROM AUTHOR]

Access to quality education for all children is important for achieving the Sustainable Development Goals especially in Africa. However, information and communication technologies (ICTs) and access to electricity have continued to be burning issues hindering access to quality education in Africa. However, empirical evidence on the impact of ICTs and access to electricity on primary education in Africa is rare. This paper, therefore, investigates the impacts of information and communication technologies and access to electricity on the education of children in Africa. The study used rich data on primary school enrolment, education expenditure, access to electricity, fixed broadband subscriptions, fixed telephone subscriptions, mobile cellular subscriptions, and individuals using the internet in Africa obtained from the World Development Indicators. Leveraging on panel autoregressive distributed lag model, we find that fixed broadband subscriptions, mobile cellular subscriptions, individuals using the internet, and access to electricity exert significant impacts on school enrolment in Africa. We find from the Granger causality test result a unidirectional causality between school enrolment and mobile phone subscription. Furthermore, we identified bidirectional causalities between school enrolment and access to electricity, education expenditure, fixed telephone subscriptions, fixed broadband subscriptions, and individuals using the internet. We conclude that information and communication technologies improve education in Africa. [ABSTRACT FROM AUTHOR]

In this paper, a quantitative, descriptive, and correlational research is carried out on the perceptions of the digital competence of Latin American engineering professors, their assessment of the didactic use of Information and Communication Technologies (ICT) in different didactic areas (interaction, communication, distribution, and administration and evaluation), and on the growth or decrease in the frequency of their use after the COVID-19 pandemic. In particular, the Latin American engineering professors' perceptions of digital competence is studied. Also, the existence of gender gaps (both in general and differentiating between private and public universities, and between professors with a more or less teaching experience) has been explored in the assessment of the perceptions of digital competence and the didactic use of ICT by engineering professors, as well as in the influence that the pandemic has had on the habits of ICT use. The results reveal that the use of ICT by engineering professors has achieved increases of over 40% in some educational activities due to the pandemic, and it has had a homogenizing effect on the frequency of use of ICT tools in the different activities. Female engineering professors have increased their use of ICT more than males, and engineering professors in private universities more than those in public universities. Consequently, it is suggested to the universities to reinforce the continuous training of engineering professors, considering the pedagogical specificities of engineering education and the necessary integration of ICT in the teaching activity of female engineering professors. [ABSTRACT FROM AUTHOR]

Technologies provide a differential value to the training process, allowing for the generation of new environments, methodologies and resources that make it possible to attend to students in a more appropriate way. This potential is especially relevant in matters of inclusion, where technology is sometimes an indispensable element for learning. In this paper we explore the main advantages of the use of technology for the attention to diversity, taking into consideration the level of digital competence of future teachers and their perceptions regarding its use for the implementation of inclusive strategies. The results suggest that participants have an intermediate level of digital competence, with differences according to gender, age and degree. It is also remarkable that they perceive inclusion as one of the main challenges of the education system and that technology can contribute to making teaching practice more inclusive, allowing it to be adapted to specific needs and highlighting the importance of teacher training in both digital competence and inclusion as an educational principle. [ABSTRACT FROM AUTHOR]

This paper aims at reviewing Information Security Awareness (ISA) practices in general and at Omani Government Agencies (OGA) in particular. It also explores the concerns and challenges that may affect their implementation, and the reasons why ISA practices remained problematic for more than a decade at the OGAs. To inform the aim of this research, the researchers employed a systematic process to review the publications that explored ISA practices in general and at OGAs in particular. As a sampling technique, the researchers created a research strategy to select relevant publications for the study. The grounded theory technique is adopted for data analysis since it provides an inductive and systematic interpretive approach to generate theoretical insights from the data. The review reveals that current ISA practices seem ineffective in meeting the needs of employees. Furthermore, a set of important ISA practices are either missing or undeveloped. The review also revealed the absence of a framework for the ISA process at OGAs. To the best of our knowledge, the present study is one of the first to conduct an in-depth review on ISA practices applied in general and at OGAs in particular. Therefore, this study contributed to the emerging field of information security by reviewing the current state of ISA practices. In addition, this research study contributed a comprehensive picture of sources dealing with vital issues of insider threats and human factors within OGAs that were indeed unclear and surrounded by various ambiguities in the past. [ABSTRACT FROM AUTHOR]

Synthesizing the advancements in technology with classroom practices depends considerably on teachers acceptance of such internet and communication technology (ICT) tools. Adequate teacher training and upgrading of their IT skills are not prioritized in developing economies leading to poor adoption of emerging technology assisted pedagogic interventions. This paper investigated the underlying characteristics of teachers acceptance of mobile friendly virtual laboratories (M-VLs) as part of a longitudinal study conducted over 5 years covering both pre-pandemic and pandemic periods. Systematic analysis of quantitative data from 650 chemistry teachers was carried out. Viewing through the theoretical lens of Unified Theory of Acceptance and Use of Technology (UTAUT2) theory, the effects of performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM) and habit (HA) on the behavioral intention (BI) and use behavior (UB) were scrutinized. Structural Equation Modeling (SEM) analysis revealed that PE, SI, and HA are the considerable predictors of the BI to use M-VLs and HA is the predictor of UB. The present study found HM influencing teacher's BI and UB before COVID-19. However during COVID-19 the FC influenced usage. Moreover, we found that the technology training focused on enhancing knowledge, skill and, access leads to teachers' are critical to empowering teachers and causing wider adoption. [ABSTRACT FROM AUTHOR]

The prevalence of e-learning systems has made educational resources more accessible, interactive and effective to learners without the geographic and temporal boundaries. However, as the number of users increases and the volume of data grows, current e-learning systems face some technical and pedagogical challenges. This paper provides a comprehensive review on the efforts of applying new information and communication technologies to improve e-learning services. We first systematically investigate current e-learning systems in terms of their classification, architecture, functions, challenges, and current trends. We then present a general architecture for big data based e-learning systems to meet the ever-growing demand for e-learning. We also describe how to use data generated in big data based e-learning systems to support more flexible and customized course delivery and personalized learning. [ABSTRACT FROM AUTHOR]

Professional development programs for teachers in higher education are often characterized by top-down approaches, which fail to make appreciable differences in teaching practices. This study uses a qualitative approach to explore activity-oriented design (AOD) as an instrument for collaborative learning in higher education teacher professional development. We examine Teknosofikum, an ongoing project developed in Denmark along three iterations, involving a total of 64 course participants (42 in the hybrid format; 22 online). The study applies the methodology of design-based research: data was collected via 15 semi-structured group interviews, online forums, and field notes/recordings from online meetings and onsite workshops. Data analysis follows the methodology of grounded theory and evidence is given significance inductively, based on contextual data. Four activities were selected to assess the potential of AOD methods in enhancing teacher collaboration, with different aims reflection, discussion, theory-practice alignment, and participation. Our analysis revolved around three main categories: trust, deep interaction, and shared beliefs/values. The results show how collaborative group work activities have improved trust and knowledge-sharing among participants and have contributed to creating a safe learning environment. The paper concludes that AOD methods could better assist educational designers in promoting professional development courses that aim at enhancing teacher collaboration in higher education. [ABSTRACT FROM AUTHOR]

Since the Covid-19 pandemic, there has been an increasing growing need for learning experience or instructional designers. As a result, online courses on user experience (UX) design for learning are in demand to prepare those much-needed professionals. This paper reports the first circle of educational design research (EDR) on such a completely online problem-based course using group contracts and peer-evaluations to promote collaborations. Multiple datasets were collected from a range of data sources from a graduate-level course and were analyzed by two researchers. The study yielded several meaningful results: (1) group contracts helped students work smoothly and keep goals focused on collaborative learning in PBL; (2) the instructor could facilitate the group formation process; (3) peer evaluations helped group collaboration and monitoring; and (4) collaborative technologies are critical for collaboration. The findings also revealed important design principles for collaborative learning in PBL that can be used in similar courses. In addition, this study provides a successful example of how to teach UX design in an online PBL environment, and sheds light on how to further improve similar practices while contributing to the limited body of research on UX design for learning. [ABSTRACT FROM AUTHOR]

Authentic context is a physical environment reflecting the knowledge application in the real world. In this study, we developed a tablet-based application, Ubiquitous Fraction (U-Fraction), to help fractions learning with authentic contextual support. Three topics were designed to learn fractions concept, fractions simplification, and fractions addition/subtraction. The learning achievement was evaluated by three variables: understanding fraction and fraction representation to evaluate fractions concept and fractions simplification, and problem solving to evaluate the three topics. This study used two groups of experimental research. The experimental group (EG) learned fractions using U-Fraction in authentic contexts, while the control group (CG) learned fractions using the traditional teaching method and paper-based assignment. The results showed that EG significantly outperformed CG. Furthermore, it was found that learning behaviors of EG had significant correlation among quantity of assignment, annotations of assignment, and post-test. Two assessment mechanisms, peer and teacher assessments using scaffoldings based on multiple representations (i.e., linguistic, logic mathematics, and visual representation), were employed to help assessment and improve the assessment results. It was found that the scaffoldings can help both peer and teacher assessments, which significantly correlated with post-test. Therefore, multiple representations and scaffoldings were helpful to improve students' learning and peer assessment. Students also perceived positively toward using U-Fraction in terms of usefulness, ease of use, ease of learning, and satisfaction of the usability questionnaire. These imply that fraction learning should be designed in a way that students can apply their knowledge in authentic contexts by taking pictures and making multiple representations. [ABSTRACT FROM AUTHOR]

This study investigated a digital reform initiative, rated excellent by the government, of one higher education institution (HEI) in an Arab State in the Gulf. The focus of the study was to develop a digital typology, while exploring the leadership attributes that characterized the core leadership team, as they accomplished the migration towards a digital culture in one year, within a context where faculty members showed resistance against digitalization. The study was conducted immediately after the implementation of the initiative that took place over the course of one year, just before the Covid-19 pandemic. Semi-structured interviews were conducted with all the six key individuals in the leadership team who led this initiative. Data was analyzed using content-based analysis. Findings of the study were used to synthesize a 5D typology for digital leadership attributes: (1) Digital competence; (2) Digital culture; (3) Digital Differentiation; (4) Digital governance; and (5) Digital advocacy. The paper provides in depth discussion how these attributes supported the adaptive ability of a Higher Education Institution towards accepting digitalization. [ABSTRACT FROM AUTHOR]

Grading assignments is inherently subjective and time-consuming; automatic scoring tools can greatly reduce teacher workload and shorten the time needed for providing feedback to learners. The purpose of this paper is to propose a novel method for automatically scoring student responses to picture-cued writing tasks. As a popular paradigm for language instruction and assessment, a picture-cued writing task typically requires students to describe a picture or pictures. Correspondingly, the automatic scoring methods must measure the link(s) between visual pictures and their textual descriptions. For this purpose, we first designed a picture-cued writing test and collected nearly 4 k responses from 279 K12 students. Based on these responses, we then developed an AI scoring model by incorporating the emerging cross-modal matching technology and some NLP algorithms. The performance of the model was evaluated carefully with six popular measures and was found to demonstrate accurate scoring results with a small mean absolute error of 0.479 and a high adjacent-agreement rate of 90.64%. We believe this method could reduce the subjective elements inherent in human grading and save teachers' time from the mundane task of grading to other valuable endeavors such as designing teaching plans based on AI-generated diagnosis of student progress. [ABSTRACT FROM AUTHOR]

The increasing daily use of Online Social Networks (OSN) around the world leads to more issues related to user privacy behaviour in this attractive environment. While users can get many benefits by using OSN services, they have many concerns regarding their information privacy at the same time. Despite their privacy concerns, users are still using these platforms and still sharing more personal information or self-disclosing. The main objective of this research is to propose a conceptual model that is built based on a cost–benefit analysis of the privacy calculus theory to explain user privacy behaviour in the OSN environment. Both paper and online questionnaires were created to collect data directly from active users of the Facebook platform in Universiti Sains Malaysia (USM). The total number of respondents was two hundred and twenty-five (225). The PLS-SEM technique was applied to test the research hypotheses and assess the proposed research model. The four research hypotheses are all supported, negative relationships have been found between the privacy concerns variable and both self-disclosure amount (β = -0.213) and self-disclosure depth (β = -0.232) variables. While positive relationships are found between the perceived benefits variable and h of self-disclosure amount (β = 0.445) and self-disclosure depth (β = 0.353) variables. [ABSTRACT FROM AUTHOR]

This study aims to examine adaptability for educational games in terms of adaptation elements, components used in creating user profiles, and decision algorithms used for adaptation. For this purpose, articles and full-text papers in Web of Science, Google Scholar, and Eric databases between 2000–2021 were searched using the keywords "educational games", "serious games", "game-based learning", "adapt*", "player modeling", "user modeling". After applying the inclusion and exclusion procedures of studies accessed in the search, 26 studies were included in the study. The studies were analyzed in line with the themes determined for the components used in the adaptation of educational games. According to the results, adaptive educational game design was made for a wide variety of fields such as programming teaching, physics, mathematics, computational thinking, and logic. As for adaptive factors; It was determined that adaptations were made for the game, educational content, interface, and non-player character (NPC) behaviors. It is understood that pre-game adaptation and in-game adaptation methods are used as adaptation types. Finally, it is seen that Bayesian networks, artificial neural networks, fuzzy logic, deep learning, item response theory, and decision tree methods are preferred as decision systems in the adaptation process. The findings of this literature review can facilitate the design process by providing a roadmap for researchers interested in adaptive educational game design. [ABSTRACT FROM AUTHOR]

Nowadays, the improvement of digital learning with Artificial Intelligence has attracted a lot of research, as it provides solutions for individualized education styles which are independent of place and time. This is particularly the case for computer science, as a tutoring domain, which is rapidly growing and changing and as such, learners need frequent update courses. In this paper, we present a thorough evaluation of a fuzzy-based intelligent tutoring system (ITS), that teaches computer programming. The evaluation concerns multiple aspects of the ITS. The evaluation criteria are: (i) context, (ii) effectiveness, (iii) efficiency, (iv) accuracy, (v) usability and satisfaction, and (vi) engagement and motivation. In the evaluation process students of an undergraduate program in Informatics of the University of Piraeus in Greece participated. The evaluation method that was used included questionnaires, analysis of log files and experiments. Also, t-tests were conducted to certify the validity of the evaluation results. Indeed, the evaluation results are very positive and show that the incorporated fuzzy mechanism to the presented ITS enhances the system with Artificial Intelligence and through this, it increases the learners' satisfaction and new knowledge learning and mastering, improves the recommendation accuracy of the system, the efficacy of interactions, and contributes positively to the learners' engagement in the learning process. [ABSTRACT FROM AUTHOR]

Computational thinking is considered to be an important competence in the intelligent era, and the incorporation of computational thinking as an integral part of school education beginning in childhood has been proposed. However, the ways in which computational thinking can be taught more effectively the context of in K-12 programming teaching remain unclear. This paper reports the results of a meta-analysis of 28 empirical studies on K-12 programming teaching that were published in international education journals in the 21st century to determine which teaching methods and programming tools are most effective in promoting the computational thinking of K-12 students. The results show that (1) programming teaching can promote the improvement of K-12 students' computational thinking (ES = 0.72, z = 9.9, P < 0.01), with an overall effect at the upper-middle level (95% CI[0.60,0.83]); (2) scaffolding programming (ES = 1.84, z = 11.9, P < 0.01) and problem-based programming (ES = 1.14, z = 5.57, P < 0.01) are the most effective teaching methods and can significantly promote the development of K-12 students' computational thinking (chi2 = 40.58, P < 0.01); (3) since differences in the effect of programming tools between groups are not significant (Chi2 = 6.47, P = 0.09), it is impossible to determine which programming tools are most effective; and (4) intervention duration (ES = 0.72, z = 11.9, P < 0.05, 95% CI[0.60, 0.83]) and learning scaffold (ES = 0.83, z = 6.27, P < 0.05, 95% CI[0.57, 1.09]) are both key moderating variables that affect the improvement of computational thinking. Based on these results, suggestions are provided for future research and practice. [ABSTRACT FROM AUTHOR]

Sign language is the natural way of communication of speech and hearing-impaired people. Using Indian Sign Language (ISL) interpretation system, hearing impaired people may interact with normal people with the help of Human Computer Interaction (HCI). This paper presents a method for automatic recognition of two-handed signs of Indian Sign language (ISL). The three phases of this work include preprocessing, feature extraction and classification. We trained a BPN with Histogram Oriented Gradient (HOG) features. The trained model is used for testing the real time gestures. The overall accuracy achieved was 89.5% with 5184 input features and 50 hidden neurons. A deep learning approach was also implemented using AlexNet, GoogleNet, VGG-16 and VGG-19 which gave accuracies of 99.11%, 95.84%, 98.42% and 99.11% respectively. MATLAB is used as the simulation platform. The proposed technology is used as a teaching assistant for specially abled persons and has demonstrated an increase in cognitive ability of 60–70% in children. This system demonstrates image processing and machine learning approaches to recognize alphabets from the Indian sign language, which can be used as an ICT (information and communication technology) tool to enhance their cognitive capability. [ABSTRACT FROM AUTHOR]

This paper, which seeks to investigate ICT-related training and support programmes for information professionals, becomes essential due to multifarious tasks that require adequate ICT skills, knowledge and application in a dynamic context to function better. This paper adopted the quantitative research approach. The quantitative approach was survey, using a questionnaire to collect data from respondents in selected university libraries in Africa. Findings revealed that ICT-related training and support programmes offered to information professionals helped to improve current practices of library operations and service delivery to users. Re-skilling becomes significant due to the existing phenomenon of pedagogical learning, thus leading to the creation and harvesting of knowledge among information professionals. The exposure, experience, knowledge and skills acquired serve as defence for information professionals in the application and use of ICT-related tools of hardware and software, irrespective of the context. Embracing continuous acquisition of knowledge and skills to navigate and sustain dynamism in the work place becomes a necessity. [ABSTRACT FROM AUTHOR]

The current study examines students' coping process of a forced technological intervention in academic outcome assessment in a higher education setting. A mixed-method approach was used to study 246 post-graduate students' post-usage behaviour of electronic tablet-PC exams and examined their end-user satisfaction. This is an empirical study grounded in the Coping Model of User Adaptation (CMUA). Respondents of the study comprise of post-graduate students, who were exposed to an innovative digital device for writing descriptive exams as a substitute to the conventional paper-mode exam. Data were analyzed using SPSS and Nvivo. Findings indicate that problem-focused coping has a significant influence on end-user satisfaction, and on the contrary emotion-focused coping is insignificant among the students. The study offers insights into those institutions, which are aspiring to advance with similar interventions in academic outcome assessment. The study contributes to the literature on technostress, coping strategy, and end-user satisfaction of ICT. [ABSTRACT FROM AUTHOR]

Machine Learning concept learns from experiences, inferences and conceives complex queries. Machine learning techniques can be used to develop the educational framework which understands the inputs from students, parents and with intelligence generates the result. The framework integrates the features of Machine Learning (ML), Explainable AI (XAI) to analyze the educational factors which are helpful to students in achieving career placements and help students to opt for the right decision for their career growth. It is supposed to work like an expert system with decision support to figure out the problems, the way humans solve the problems by understanding, analyzing, and remembering. In this paper, the authors have proposed a framework for career counseling of students using ML and AI techniques. ML-based White and Black Box models analyze the educational dataset comprising of academic and employability attributes that are important for the job placements and skilling of the students. In the proposed framework, White Box and Black Box models get trained over an educational dataset taken in the study. The Recall and F-Measure score achieved by the Naive Bayes for performing predictions is 91.2% and 90.7% that is best compared to the score of Logistic Regression, Decision Tree, SVM, KNN, and Ensemble models taken in the study. [ABSTRACT FROM AUTHOR]

Recent advances in sensor technology, including eye-gaze tracking, have introduced the opportunity to incorporate gaze into student modelling within an embodied learning context. The produced multimodal data is used to uncover cognitive, behavioural, and affective processes during the embodied learning activity. However, the use of eye-tracking data presenting visual attention to understand students' behaviours and learning performance during engagement with tangible learning activity is rather unexplored. Therefore, this paper explores the integration of eye-gaze features to predict students' learning performance during an embodied activity. We present an in-situ study where 110 primary school students (aged 8–9 years), solved a tangible learning activity for learning human body anatomy. During the experiment, students' learning experience was monitored by collecting their eye-tracking data, learning profiles, academic performances, and time to complete the activity. We applied predictive modelling to identify the synergies between eye-gaze features and students' learning performance. The obtained results suggest that combining eye-gaze tracking with learning traces and behaviour attributes may support an accurate prediction of students' learning performance. This research sheds light on the opportunities offered in the intersection of eye-gaze tracking with learning traces, and its possible contribution to investigating students' behaviour within an embodied learning context. [ABSTRACT FROM AUTHOR]

This research examines the effect of having a tracking technology in a learning management system (LMS) that reports the effect of perceiving other students' interactions on a learner's intention to keep using LMS in the future. The main underlying theory is herd behaviour theory which argues that crowd behaviour affects the perceptions of the observers. In this paper, we proposed and found that tracking technology will affect a learner's perceptions of cognitive absorption and that perception of self-regulation from using an LMS. These perceptions are found to influence the learner's intention to keep using the LMS in the future positively. This research developed a new tracking technology in response to weaknesses noted in the literature and validated by interviewing teachers. Its effects were tested on 151 university students taking a computer science module. This research contributes to knowledge by integrating herd behaviour theory into the design of LMS and offers a new perspective on learners' interactions with educational technologies. [ABSTRACT FROM AUTHOR]

Due to the growing demand for information technology skills, programming education has received increasing attention. Predicting students' programming performance helps teachers realize their teaching effect and students' learning status in time to provide support for students. However, few of the existing researches have taken the code that students wrote into consideration. In fact, code is informative and contains lots of attributes. Student programming performance can be better understood and predicted by adding code information into student profiles. This paper proposed a student profiles model to describe students' characteristics, which contains the code information and then was used as the input of a deep neural network to predict the programming performance. By comparing different machine learning techniques and different combinations of dimensions of student profiles, the experimental results show that a four-layer deep neural network fed with all available dimensions of student profiles has achieved the best prediction with RMSE 12.68. [ABSTRACT FROM AUTHOR]