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In an immersive virtual reality (IVR) environment, this study investigated: (1) the role of learner characteristics in various learning and psychological outcomes, including knowledge retention, perceived learning, cognitive load, self-efficacy, enjoyment, presence, and usefulness; and (2) the relationship among these intended outcomes. Forty adult participants experienced an IVR nature trail tour involving science learning topics, followed by a knowledge test and multiple surveys. Multivariate analysis of covariance results indicated age by gender interaction effects on perceived presence and usefulness as well as an age by IVR prior experience interaction effect on perceived presence. Additionally, multiple correlational relationships were detected among the intended outcomes. This study contributes to the limited research on the role of learner characteristics in STEM learning and psychological outcomes in IVR environments. [ABSTRACT FROM AUTHOR]

In today’s world, with the rapid development of information technology and scientific education, data technology has triggered important changes in ideological and political education in colleges and universities, effectively promoting the transformation of educational concepts, ways of thinking, educational methods, and practice modes. Based on the research background under big data, this study investigates the traditional knowledge-tracking model, introduces the attention mechanism and the characteristics of ideological and political learners on the basis of the traditional model, and proposes an improved knowledge-tracking model. At the same time, a mobile teaching platform was constructed, then the improved knowledge tracking model was tested, and the effect of the knowledge platform application on the relevant dataset was explored. The results show that using the optimized knowledge state tracking model, the teacher’s teaching time can be adjusted according to the students’ state, and there is a good effect on the prediction of students’ grades, and the average grade of the students is only 2-6 points of error from the predicted grades. In terms of model application accuracy, the average value of low accuracy is 6.92%, the average value of medium accuracy is 12.9%, and the average value of high accuracy is 79.79%, so the model assesses students’ knowledge status with high accuracy. Finally, the optimized model was used to analyze the learning effect of the students and to conduct a survey on the effect of using satisfaction, and the survey concluded that the students were more satisfied with the model.

Nowadays, the need for e-learning is amplified, especially after the Covid-19 pandemic. E-learning platforms present a solution for the continuity of the learning process. Learners are using different platforms and tools for learning. For this, it is necessary to model the learner for the personalization of the learning environment according to his needs, and characteristics, which will allow having a more effective and efficient environment. The existing literature maintains that the learner model represents the basis and the key to adaptation. To achieve this goal, we propose a new adaptation aspect of the learner model by integrating relevant information such as learning style, domain-related data, assessment-related data, and affective data. It has advantages in terms of precision as it solves the problem of management uncertainty of some parameters. Our approach suggests that the combination of stereotype method, fuzzy logic, and similarity techniques is an appropriate approach for initializing and updating the learner model for learning personalization. [ABSTRACT FROM AUTHOR]

Abstract Assessing students on-the-fly is an important but challenging task for teachers. In initial teacher education, a call has been made to better prepare pre-service teachers for this complex task. Advances in technology allow this training to be done through authentic learning environments, such as video-based simulations. To understand the learning process in such simulations, it is necessary to determine how cognitive and motivational learner characteristics influence situative learning experiences, such as the perception of authenticity, cognitive load, and situational motivation, during the simulation and how they affect aspects of performance. In the present study, N = 150 pre-service teachers from German universities voluntarily participated in a validated online video-based simulation targeting on-the-fly student assessments. We identified three profiles of learner characteristics: one with above average knowledge, one with above average motivational-affective traits, and one with below average knowledge and motivational-affective traits. These profiles do not differ in the perception of the authenticity of the simulation. Furthermore, the results indicate that the profiled learners navigate differently through the simulation. The knowledgeable learners tended to outperform learners of the other two profiles by using more learning time for the assessment process, also resulting in higher judgment accuracy. The study highlights how learner characteristics and processes interact, which helps to better understand individual learning processes in simulations. Thus, the findings may be used as a basis for future simulation research with a focus on adaptive and individual support.

With the rapid spread of COVID-19 worldwide, governments of all countries declared the closure of educational institutions to control its transmission. As a result, institutions were under pressure to offer online education opportunities so that students could continue their education without interruption. The unintended, hasty and unknown duration of the strategy encountered challenges at all pedagogical levels, especially for students who felt stressed out by this abrupt shift, resulting in the decline of their academic performance. Hence, it is necessary to comprehend the approach that might improve students' involvement and performance in online learning. In this context, the current study used four models to understand the phenomenon: the Task Technology Fit (TTF), the DeLone and McLean Model of Information Systems Success (DMISM), the Technology-to-Performance Chain model (TPC) and the Technology Acceptance Model (TAM). The data for this study were obtained from 404 university students from the top ten universities of Pakistan. The results analyzed using structural equation modeling (SEM) show that learner characteristics positively predict performance through user satisfaction and task technology fit mediating function. Moreover, learner characteristics were also observed to have a significant positive influence on the academic performance of the students, with the mediating functions of user satisfaction and actual usage of the system. Likewise, perceived learning moderated the relationship between learner characteristics and user satisfaction. This research work provides policymakers with a profound framework that emphasizes how employing online learning technologies can strengthen the academic potential of students. [ABSTRACT FROM AUTHOR]

In addition to a face-to-face classroom learning environment, today's learners in higher education are likely to have also experienced a blended learning or an online learning environment. These learning environments not only differ in their delivery modes, but also learning activities, class interactions, assessment approaches, etc. Learners tend to have differing perceptions about the effectiveness of different learning environments. This study therefore investigates whether the reasons learners like or dislike a learning environment reveal learner characteristics that may explain why some learners are more inclined towards a particular learning environment. This study also examines whether learner demographics influence learner characteristics and their preference for a particular learning environment. Using an exploratory sequential mixed methods research design, this study first conducted several focus group discussions and then administered an online questionnaire survey to collect input from students at a local university. Analyses derived four learner characteristics (i.e. desire for direct support, digital readiness, learning independence, and online hesitancy) based on the reasons why the students liked or disliked face-to-face classroom learning, blended learning, or online learning environments. A cluster analysis further distinguished the students into three groups (i.e. classroom learners, insecure learners, and online learners) based on the four learner characteristics. Analyses also found that learners' demographics largely had no effect on learners' characteristics and their preference for a particular learning environment. The findings suggest that learner characteristics may provide a clue to why certain learners have a preference for a face-to-face classroom learning, a blended learning, or an online learning environment. A better understanding of the relationship between learner characteristics and learners' inclination towards a particular learning environment can be helpful to educational institutions and academics to design a range of engaging learning activities for learners with different characteristics. [ABSTRACT FROM AUTHOR]

It is frequently assumed that learner characteristics (e.g., reading skill, self-perceptions, optimism) account for overestimations of text comprehension, which threaten learning success. However, previous findings are heterogenous. To circumvent a key problem of previous research, we considered cognitive, metacognitive, motivational, and personality characteristics of learners (N = 255) simultaneously with regard to their impact on the judgment biases in prediction and postdiction judgments about factual and inference questions. The main results for the factual questions showed that men, lower reading skill, working memory capacity, and topic knowledge, yet higher self-perceptions of cognitive and metacognitive capacities yielded stronger overestimations for prediction judgments. For inference questions, a lower reading skill, higher self-perceptions of metacognitive capacities, and a higher self-efficacy were related to stronger overestimations for prediction and postdiction judgments. A higher openness was a risk factor for stronger overestimations when making predictions for the inference questions. The findings demonstrate that learner characteristics are a relevant source of judgment bias, which should be incorporated explicitly in theories of judgment accuracy. At the same time, fewer learner characteristics were actually relevant than previous research suggests. Moreover, which learner characteristics impact judgment bias also depends on task requirements, such as factual versus inference questions. [ABSTRACT FROM AUTHOR]

Student characteristics affect their willingness and ability to acquire new knowledge. Assessing and identifying the effects of student characteristics is important for online educational systems. Machine learning (ML) is becoming significant in utilizing learning data for student modeling, decision support systems, adaptive systems, and evaluation systems. The growing need for dynamic assessment of student characteristics in online educational systems has led to application of machine learning methods in modeling the characteristics. Being able to automatically model student characteristics during learning processes is essential for dynamic and continuous adaptation of teaching and learning to each student's needs. This paper provides a review of 8 years (from 2015 to 2022) of literature on the application of machine learning methods for automatic modeling of various student characteristics. The review found six student characteristics that can be modeled automatically and highlighted the data types, collection methods, and machine learning techniques used to model them. Researchers, educators, and online educational systems designers will benefit from this study as it could be used as a guide for decision-making when creating student models for adaptive educational systems. Such systems can detect students' needs during the learning process and adapt the learning interventions based on the detected needs. Moreover, the study revealed the progress made in the application of machine learning for automatic modeling of student characteristics and suggested new future research directions for the field. Therefore, machine learning researchers could benefit from this study as they can further advance this area by investigating new, unexplored techniques and find new ways to improve the accuracy of the created student models.

Assessing students on-the-fly is an important but challenging task for teachers. In initial teacher education, a call has been made to better prepare pre-service teachers for this complex task. Advances in technology allow this training to be done through authentic learning environments, such as video-based simulations. To understand the learning process in such simulations, it is necessary to determine how cognitive and motivational learner characteristics influence situative learning experiences, such as the perception of authenticity, cognitive load, and situational motivation, during the simulation and how they affect aspects of performance. In the present study, N = 150 pre-service teachers from German universities voluntarily participated in a validated online video-based simulation targeting on-the-fly student assessments. We identified three profiles of learner characteristics: one with above average knowledge, one with above average motivational-affective traits, and one with below average knowledge and motivational-affective traits. These profiles do not differ in the perception of the authenticity of the simulation. Furthermore, the results indicate that the profiled learners navigate differently through the simulation. The knowledgeable learners tended to outperform learners of the other two profiles by using more learning time for the assessment process, also resulting in higher judgment accuracy. The study highlights how learner characteristics and processes interact, which helps to better understand individual learning processes in simulations. Thus, the findings may be used as a basis for future simulation research with a focus on adaptive and individual support. [ABSTRACT FROM AUTHOR]

Learner corpus research has a strong tradition of collecting metadata. However, while we tend to collect rich descriptive information about learners on directly measurable variables such as age, year of study, and time spent abroad, we frequently do not know much about learner characteristics that cannot be measured directly (and that thus need to be measured through questionnaires and tests) such as language aptitude, working memory, and motivation, which have been identified as important variables in neighboring fields such as Second Language Acquisition. In this position piece, we (i) join the proponents of increased focus on learner characteristics in LCR in arguing in favor of collecting information about such variables and (ii) introduce an analytical framework that can be used to model these variables. Specifically, the primary focus of this paper is to discuss the concept of latent variables as it relates to LCR and show how their standard form can be used to model learner characteristics within the structural equation modeling analytical framework. [ABSTRACT FROM AUTHOR]

A primary affordance of virtual reality (VR) headsets is to give the user spatial presence or the illusion of being in the virtual environment. Although considerable research connects VR to spatial presence, spatial awareness, and spatial ability, little is known about how users develop spatial presence in VR learning environments. This study addresses that gap by exploring spatial presence experience construction in a VR educational game and investigating whether users' knowledge, game experience, and VR experience impact the establishment of spatial presence. In this study, 56 high school students played an immersive 3D VR cell biology game where players search for clues within a virtual cell to diagnose the cell. Findings suggest that players' perceptions of spatial presence are linked to how they allocate their attention during the game, their level of interest in cellular biology, and their visual-spatial acuity, but are not linked to their game experience, VR experience, or prior knowledge of the content area. These results indicate that well-scaffolded, engaging virtual environments can foster spatial presence among users, regardless of prior knowledge or experience, and gives practitioners clues about how to design VR learning environments. [ABSTRACT FROM AUTHOR]

Online discussion forums are an essential and standard setup in online courses to facilitate interactions among learners. However, learners' inadequate participation in online discussion forums is a long-standing challenge, which necessitates instructor intervention and the design consideration of online learning platforms. This research proposes and studies the role of mandatory participation, i.e., learners' participation in online course forums by instructors' requirements, in fostering their voluntary participation and boosting their learning performance. This novel effect link between mandatory participation and voluntary participation has not been assessed in previous research. An empirical study is conducted using a large-scale dataset of 27,767 learners from a leading massive open online course (MOOC) platform in China. The findings indicate that besides its direct effect on learning performance, learners' mandatory participation has a significant positive effect on their voluntary participation in online course forums, enhancing learning performance. Moreover, the effect of mandatory participation on voluntary participation varies across learner groups, being more prominent for early registrants than late registrants and part-time learners than full-time learners. This research contributes to the online learning literature by introducing mandatory participation as a viable approach to foster voluntary participation and boost learning performance through enhanced voluntary participation. It provides evidence on the effectiveness of the novel design feature of MOOC platforms that enables and facilitates the mandatory participation mechanism in online learning. [ABSTRACT FROM AUTHOR]

Introduction:The purpose of this study was to investigate the impact of learner characteristics through mediating the usefulness of ICT tools on risky attitudes and entrepreneurial intention. Materials and Methods:The research method was descriptive-correlational (causal type) and the statistical population was 913 female high school students in Abadeh and 210 students in a single sample using Power G sampling software and single-stage cluster random sampling. It was. Data collection tools in this study were Entrepreneurial Learning Questionnaire, by Tang et al. (2010), ICT, by Agostinho (2002), Entrepreneurial Venture Risk, by Iverson (2004), Entrepreneurial Development, by Hisrich(1988) and Entrepreneurial Goals, by Scott and et al. (2003) confirmed that its content validity and reliability through Cronbach's alpha were estimated to be 0.705, 0.721, 0.704, 0.821, and 0.813, respectively. SPSS 26 software was used to test the hypotheses in inferential statistics using structural equation modeling with Smart PLS3 software. Findings: The findings showed that learner entrepreneurial characteristics, on entrepreneurial intention (P 0.05). Conclusion:It seems that entrepreneurship development, through the initiative and creativity in entrepreneurial projects, as well as encouraging students to change their attitude towards entrepreneurship and creative work, is achieved through more entrepreneurship education.

To learn and comprehend the large amount of information in gross anatomy, undergraduate students must self-regulate their learning to be properly prepared for the exams within the available time. Even though there are many studies on learning strategies and their influence on test results and motivation, the aim of this study is to investigate characteristics of learning strategies in detail and in relation to the anatomy course of first semester students and how their use is related to anatomy test performance. For assessing the learning strategies, we used the short version of the questionnaire "Learning Strategies of University Students" (LIST-K) (Klingsieck, 2018). Further, we investigated potential influences of motivation and resources used during the self-regulated learning process. The participants in this study (N = 108) filled in the above-mentioned questionnaire LIST-K and a written multiple-choice anatomy test. A k-means cluster analysis revealed three groups of students differing in their self-reported use of learning strategies. Students used either (1) predominantly metacognitive and resource-related strategies, (2) predominantly cognitive strategies, or (3) no specific learning strategies at all. We found no significant overall relationships between the use of learning strategies and test performance. A stepwise linear regression identified the use of cognitive learning strategies (β =.269) as a significant predictor for test performance (R² =.149, p =.003), possibly as these specific learning strategies help with a systematic and effective approach while studying anatomy and retrieving large amount of memorized information. Further, motivation was identified as a negative predictor (β = −.277), which might be a result of the short time periods students have to study for exams. Overall findings underline the importance of self-regulated learning as a positive predictor for academic performance. By understanding these factors, a more student-centered approach could be adopted by educators to improve medical education and equip students with valuable approaches for their continuous education, even beyond university. [ABSTRACT FROM AUTHOR]

Online discussion forums are an essential and standard setup in online courses to facilitate interactions among learners. However, learners’ inadequate participation in online discussion forums is a long-standing challenge, which necessitates instructor intervention and the design consideration of online learning platforms. This research proposes and studies the role of mandatory participation, i.e., learners’ participation in online course forums by instructors’ requirements, in fostering their voluntary participation and boosting their learning performance. This novel effect link between mandatory participation and voluntary participation has not been assessed in previous research. An empirical study is conducted using a large-scale dataset of 27,767 learners from a leading massive open online course (MOOC) platform in China. The findings indicate that besides its direct effect on learning performance, learners’ mandatory participation has a significant positive effect on their voluntary participation in online course forums, enhancing learning performance. Moreover, the effect of mandatory participation on voluntary participation varies across learner groups, being more prominent for early registrants than late registrants and part-time learners than full-time learners. This research contributes to the online learning literature by introducing mandatory participation as a viable approach to foster voluntary participation and boost learning performance through enhanced voluntary participation. It provides evidence on the effectiveness of the novel design feature of MOOC platforms that enables and facilitates the mandatory participation mechanism in online learning.

Background: The development of learner models in learning management systems is among the most significant steps in designing personalized e-learning environments. The primary purpose of this modeling is to extract user characteristics in order to personalize the learning process based on learners’ needs, learning style, personality, and individual circumstances. Methods: The present study provides a review of published literature over the past 20 years in academic databases including IEEE, Sciencedirect, Wiley, and Springer. The search was limited to the studies on the personalization of e-learning environments based on learner characteristics, specifically the ones providing a reliable method for integrating these characteristics, as appropriate input variables, in the design of personalized e-learning systems. Results: This study proposed a new method of classifying the learner characteristics as the variables for designing a personalized e-learning system. A total of 111 papers were considered for analysis. In the end, 22 influential learner characteristics were extracted and classified into six subcategories, namely cognitive, motivational, behavioral, emotional, metacognitive aspects, and combined domains. The proposed classification method was also compared with available related categorizations to demonstrate this method’s advantage in designing a personalized e-learning environment. Conclusion: The findings represent the learning criteria that can be utilized in designing adaptive learning systems. Moreover, it can also aid other researchers in this field to achieve a better perspective in learner modeling. Applying these characteristics as input design variables in personalized e-learning systems can result in a better solution for personalization.

Background: Business simulation as an instructional tool helps in developing integrative thinking and decision making skills. It is being taught to audiences who differ considerably in age, work experience (learner characteristics) and learning styles. The use of simulations is likely to grow further with advancements in internet technology and the fact that simulations are very amenable to remote modes of instruction. Aim: This study aims to assess how learner characteristics and learning styles impact business simulation performance. It further assesses the combined effect of learner characteristics and learning styles on performance in business simulations, we specifically consider the manner in which learning styles moderate the impact of learner characteristics (age) on simulation performance. Method: The study was conducted with 605 students of full time MBA and executive MBA programs with age group varying from 21 years to 53 years. They were taught using the same business simulation by CAPSIM. The learning styles were measured using Felder-Solomon's instrument 'Index of learning style'. Regression analysis was conducted with predictor variables of learner characteristics and learning styles and outcome variable of simulation performance. The moderating effect of specific learning styles on learner characteristics was identified. Results: The findings indicate that age is a significant predictor of simulation performance (younger, tech savvy students do better). Also, the use of reflective learning style enables better performance in business simulations. Older students are able to draw on experience and benefit more from reflective learning, for business simulations which involve integration across functions. Conclusion: The study enhances our conceptual understanding of the factors enabling performance in business simulations and provides specific direction on how instructors must adapt facilitation approaches for different age groups of participants. Reflection is important for learning with business simulations; hence, the reflective learning style should be encouraged particularly among older students. [ABSTRACT FROM AUTHOR]

This case study was intended to explore whether wearable device use is associated with their demographic factors (e.g., device ownership and gender), using undergraduate students in a Hispanic Serving Institution. Preliminary findings of this two-way contingency table analysis suggested that students who own the device(s) are more likely to use it for school. Males are more likely to use the wearables for learning in spite of a marginal effect size. Implications and recommendations are discussed. [ABSTRACT FROM AUTHOR]

Drawing on the assumptions of control-value theory (CVT), the current study examined whether the four facets of test anxiety (emotionality, worry, interference, lack of confidence) serve as intervening variables between learners' characteristics (performance-approach goals, mastery experiences) and learning behaviour (perseverance and diligence), which, in turn, should predict academic performance. Based on a sample of 696 Italian university students (58.11% female; Mage = 21.64, SDage = 4.04), structural equation modelling largely supported the proposed structure of relationships. Mastery experiences and performance-approach goals were differentially related to the four facets of test anxiety. Regarding test anxiety, lower levels of interference and lack of confidence, yet higher levels of worry, were associated with a greater use of perseverance and diligence, which in turn, predicted a better grade. The findings suggest that CVT provides a useful framework to explore the differential role of test anxiety facets between learners' characteristics and learning behaviour, which may be beneficial for performance. [ABSTRACT FROM AUTHOR]

This mixed‐methods study investigates the attitudes of middle and high school World Language (WL) teachers in Iowa regarding teaching students with disabilities (SWDs) as well as factors that relate to these attitudes. The study uses data from surveys of 41 Iowa WL teachers and semistructured interviews with eight. Survey data were analyzed using descriptive and inferential statistics and interview data were analyzed using thematic analysis. These findings were then combined for mixed methods analysis of WL teachers' attitudes toward teaching SWDs and factors related to differences in attitudes. Findings suggested middle and high school WL teachers in Iowa had positive attitudes toward the inclusion of SWDs in their classes, but there were nuances to this support. Several factors were found to relate to participants' attitudes, including their perceptions of the usefulness of their preservice and in‐service training, the level of administrative support, and the structure of the WL program. The Challenge: Federal legislation like the Individuals with Disabilities Education Act and position statements on diversity and inclusion by ACTFL support the inclusion of students with disabilities in general education classes, but what do World Language teachers think? What impacts these beliefs? Are World Language teacher attitudes similar to other content areas? [ABSTRACT FROM AUTHOR]

This large‐scale study used a survey to collect data on K–12 world language programming in Massachusetts public schools. Building off work by Pufahl and Rhodes (2011), this study focused on world language programs, program types, and languages offered, as well as student exclusion, program leadership, and the Seal of Biliteracy. The study resulted in 188 districts represented in the final data set, which was analyzed using descriptive statistics. Results indicate comparable findings to national data in terms of program and language offerings, with shifts in program type. Data further revealed patterns of student exclusion and trends in offering the Seal of Biliteracy. Although programs are most often led by a world language specialist, school principals are more likely responsible for teacher evaluation. Survey data were collected at the beginning of school closures due to COVID‐19, capturing a picture of K–12 world language education and a point of comparison for future research. The Challenge: How can we make progress in world language education without understanding K–12 programming? How can we lead change without knowing who the K–12 program leaders are and what responsibility they hold? And how can we advocate for inclusion of more students in our programs without knowing who is being excluded? [ABSTRACT FROM AUTHOR]

Abstract Background Understanding the impact of selection and medical education on practice intentions and eventual practice is an essential component of training a fit-for-purpose health workforce distributed according to population need. Existing evidence comes largely from high-income settings and neglects contextual factors. This paper describes the practice intentions of entry and exit cohorts of medical students across low and high income settings and the correlation of student characteristics with these intentions. Methods The Training for Health Equity Network (THEnet) Graduate Outcome Study (GOS) is an international prospective cohort study tracking learners throughout training and ten years into practice as part of the longitudinal impact assessment described in THEnet’s Evaluation Framework. THEnet is an international community of practice of twelve medical schools with a social accountability mandate. Data presented here include cross-sectional entry and exit data obtained from different cohorts of medical students involving eight medical schools in six countries and five continents. Binary logistic regression was used to create adjusted odds ratios for associations with practice intent. Results Findings from 3346 learners from eight THEnet medical schools in 6 countries collected between 2012 and 2016 are presented. A high proportion of study respondents at these schools come from rural and disadvantaged backgrounds and these respondents are more likely than others to express an intention to work in underserved locations after graduation at both entry and exit from medical school. After adjusting for confounding factors, rural and low income background and regional location of medical school were the most important predictors of intent to practice in a rural location. For schools in the Philippines and Africa, intention to emigrate was more likely for respondents from high income and urban backgrounds. Conclusions These findings, from a diverse range of schools with social accountability mandates in different settings, provide preliminary evidence for the selection and training of a medical workforce motivated to meet the needs of underserved populations. These respondents are being followed longitudinally to determine the degree to which these intentions translate into actual practice.

Educational robots have been used in many countries as teaching assistants in elementary schools but robotic education quality is not well established in Thailand. The primary objective of this study was to identify and confirm quality dimensions in robotic education from the teachers' perspectives. The sample size was 510 teachers who were observed in Thai elementary schools. Confirmatory Factor Analysis (CFA) indicated a good fit of a six-factor model to the observed data. The construct of CFA revealed six dimensions of robotic education quality as Social interaction, Cognitive function, Teaching method, Learner characteristics, Main features and Content. Results were similar to previous studies. Prototype development of an educational robot was proposed in relation to the Thai educational context. Further research, including large random comparative studies, needs to be performed. [ABSTRACT FROM AUTHOR]

Teachers struggle to reach all students and to lead them to mastery of the various disciplines they teach. However, only a few student display persistence and tenacity to accomplish academic assignments and goals set by teachers, schools, and districts. This paper explores the concept of persistence and how to develop persistence in students. Included are four texts by Edward Deci (internal motivation), Carol Dweck (mindset), Angela Duckworth (grit), and Daniel Pink (drive) which shed light on the characteristics of persistence and suggest strategies for teaching students how to recognize and develop persistence. Four concluding suggestions are made for transforming learning environments for the development of passion and persistence in learners. Also included is the Rubric for Learner Behavior delineating learning environment practices of successfully engaged students. [ABSTRACT FROM AUTHOR]

Catholic schools are called to serve all of God's children, including students with disabilities who require and benefit from inclusive practices. Inclusionary practices align with Catholic Social Teaching (CST), Catholic identity, and the mission of the Catholic schools. This article frames CST's foundation for inclusive practices in Catholic schools, defines disabilities and explains relevant educational terms, summarizes models of inclusion, and debunks five common misperceptions about inclusion of students with disabilities in Catholic schools. Educators will be heartened through greater clarity of theological motivation for admitting students with disabilities, provided insight about various disability characteristics to inform instructional planning, and invited to reflect on how to deliver services to all students across a continuum of least restrictive environments. [ABSTRACT FROM AUTHOR]

Several successful initiatives have resulted from the OER movement. One of them is Massive Open Online Courses (MOOCs) which is a popular learning mode as it offers an affordable and flexible way to learn. However, the evolution of the MOOCs has some challenges. One of the major problems of MOOCs is the diversity of learners and the need to personalize the content as well as the way of delivering it. The origin of this problem is the one size does not fit all. In fact, learners have different characteristics such as their learning styles, levels of knowledge, and so on. The selection of the most suitable parameters (set of complementary learners' characteristics) to be considered in learner's profile is not easy in the presence of a considerable number of learners in MOOCs. One reason is because a course can be attended by many learners with varied profiles from different regions of the world. This plurality of learner profiles makes it important to develop content that can meet the needs and objectives of each learner in MOOCS. Our solution to solve this problem consists of personalizing the content of MOOC for each learner. We propose a new approach which allows to optimize the selection of the personalization parameters and to apply the appropriate personalization strategy, based on a classification algorithm. The proposed approach aims to improve the retention rate and the quality of learning in MOOCs. This approach is validated by experiments which test its success when applied to many combinations of strategies and learner profiles. [ABSTRACT FROM AUTHOR]

Actualizing instructional intercessions to suit learner contrasts has gotten extensive consideration. Among these individual contrast factors, the observational confirmation in regards to the academic benefit of learning styles has been addressed, yet the examination on the issue proceeds. Late improvements in web-based executions have driven researchers to re-examine the learning styles in adaptive tutoring frameworks. Adaptivity in intelligent tutoring systems is strongly influenced by the learning style of a learner. This study involved extensive document analysis of adaptive tutoring systems based on learning styles. Seventy-eight studies in literature from 2001 to 2016 were collected and classified under select parameters such as main focus, purpose, research types, methods, types and levels of participants, field/area of application, learner modelling, data gathering tools used and research findings. The current studies reveal that majority of the studies defined a framework or architecture of adaptive intelligent tutoring system (AITS) while others focused on impact of AITS on learner satisfaction and academic outcomes. Currents trends, gaps in literature and ications were discussed.

It has been proven that adopting the "one size fits one" approach has better learning outcomes than the "one size fits all" one. A customized learning experience is attainable with the use of learner models, the main source of variability, in adaptive educational hypermedia systems or any intelligent learning environment. While such a model includes a large number of characteristics which can be difficult to incorporate and use, several standards that were developed to overcome these complexities. In this paper, the proposed work intents to improve learner's model representation to meet the requirements and needs of adaptation. We took IMS-LIP, IMSACCLIP and IMS-RDCEO standards into consideration and incorporated their characteristics to our proposed learner model so that it conforms to international standards. Moreover, the suggested learner model takes advantage of the semantic web technologies that offer a better data organization, indexing and management and ensures the reusability, the interoperability and the extensibility of this model. Furthermore, due to the use of ontologies, the metadata about a learner can be used by a wide range of personalization techniques to provide more accurate customization. [ABSTRACT FROM AUTHOR]

The field of adaptive e-learning is continuously developing. More research is being conducted in this area as adaptive e-learning aims to provide learners with adaptive learning paths and content, according to their individual characteristics and needs, which makes e-learning more efficient and effective. The learner model, which is a representation of different learner's characteristics, plays a key role in this adaptation. This paper presents a systematic literature review about learner modelling during the last 5 years, describing the different modelled characteristics and the adopted modelling techniques and modeling types: automatic modeling and collaborative modeling. 107 publications were selected and analyzed, and six categories of the modelled characteristics were identified. This literature review contributes to the identification of the learners' individual traits and presents the most used modelling techniques for each of them. It also identifies the latest research trends of Learner Modeling and generates future research directions in this field. [ABSTRACT FROM AUTHOR]

Although learner characteristics and item properties are known to affect students' reading comprehension performance, little research has focused on the interactions between these two types of features. This study investigated the effects of learner factors (i.e., gender, the main language spoken at home, multilingualism, and instruction on reading strategies) and item factors (i.e., item format and cognitive process), as well as their interactions, on Canadian students' performance (n = 16,688) in the reading test of PISA 2018. The results indicated that all learner and item factors significantly predicted reading comprehension. Open-response items were more difficult for male students compared to their female peers. Receiving instruction on reading strategies was most helpful in answering the understanding type of items. Students who mainly spoke the test language at home were specifically better at answering items focused on locating information, while multilingualism appeared to compensate for not speaking the test language at home. • Significant interactions were found between student characteristics and item properties in PISA 2018. • Open-response items were more difficult for male students compared to their female peers. • Speaking the test language at home was useful for answering items focused on locating information. • Multilingualism was useful in compensating for the negative effect of not speaking the test language at home. [ABSTRACT FROM AUTHOR]

In many settings, sports training can be difficult to organize, logistically complicated and very costly. Virtual environments (VE) have garnered interest as a tool to train real-world sports skills due to the realism and flexibility that they can deliver. A key assumption of VE-based training is that the learned skills and experiences transfer to the real world, but do they? Using PRISMA guidelines, this systematic review evaluated the available evidence regarding the transfer of motor skills from VE training to real-world sporting contexts. The initial search identified 448 articles, but only 4 of these articles met basic criteria necessary to assess real-world transfer. Key factors regarding the study design, learner characteristics and training environment of these studies are considered. In a relatively new area of research, the findings from these 4 articles are encouraging and provide initial support for the notion that skills training in a VE can improve real-world performance in sports. However, for a wider uptake of VEs in sports training, it is important that more research demonstrates real-world transfer. Study design recommendations are suggested for researchers, developers or trainers who are considering demonstrating real-world transfers from virtual to real-world environments.

Desirable difficulties are learning strategies that lead to more effective and durable learning even if the application produces difficulty at the moment of learning (Bjork, 1994). With this study we investigated the question which learner characteristics are linked to perception and application of those effortful strategies in self-regulated learning situations. In doing so we focused on locus of control, a construct that describes the extent to which individuals feel to have control over the outcome which arises from their own behavior (Rotter, 1975). Supporting our assumptions, internals-thus students with a stronger feeling of controllability - showed more positive attitudes towards desirable difficulties, whereas externals-thus students who suppose that external forces like chance/fate or powerful others have control over their behavior - showed no correlation. Furthermore, internals showed increased self-reported use of desirable difficulties. Contrary to prediction, external locus of control also was correlated to self-reported use of desirable difficulties. Results are discussed related to implications for the application of desirable difficulties in a real academic context regarding students with different learning characteristics, as well as to implications for further research. [ABSTRACT FROM AUTHOR]

Background and context: The variables that researchers measure and how they measure them are central in any area of research, including computing education. Which research questions can be asked and how they are answered depends on measurement. Objective: To summarize the commonly used variables and measurements in computing education and to compare them to best practices in measurement for human-subjects research. Method: Systematic literature review analyzing 197 papers published during 2013-2017 in computing education research venues. Findings: The review illuminates common practices related to: variables measured (including learner characteristics), measurements used, and type of data analysis. The paper lists standardized measurements that were used and highlights commonly used variables for which no standardized measures exist. Implications: The paper concludes with information about best practices currently being used in the community that should be continued, as well as pointing out practices that could be improved along with recommendations for how to begin to adopt those best practices. [ABSTRACT FROM AUTHOR]

The social and individual aspects of MOOCs are two sides of the same coin. However, while the majority of MOOC designs do not valorise the potential that a massive audience could bring in, several studies highlight the solo-mission mode of MOOC users’ experience. Based on implementation intention, social presence, social influence and flow theory we conceptualise our gamification design of MOOCs that embraces their social and individual aspects. We present the gamification design process, our theoretical framework, the quantitative and qualitative results of our study to identify the most suitable game elements, their conceptual design, and our recommendations. Our findings enable designers of gamification and MOOCs as well, to see these two phenomena under a new light, by referring to new theories and new game elements that were not being considered before in the design of a gamified MOOC aiming at enhancing users’ goal achievement and engagement.