Showing papers in "Computers in Education in 2021"

Comparative Analysis of Student’s Live Online Learning Readiness During the Coronavirus (COVID-19) Pandemic in the Higher Education Sector

Abstract: Amid the coronavirus outbreak, many countries are facing a dramatic situation in terms of the global economy and human social activities, including education. The shutdown of schools is affecting many students around the world, with face-to-face classes suspended. Many countries facing the disastrous situation imposed class suspension at an early stage of the coronavirus outbreak, and Asia was one of the earliest regions to implement live online learning. Despite previous research on online teaching and learning, students' readiness to participate in the real-time online learning implemented during the coronavirus outbreak is not yet well understood. This study explored several key factors in the research framework related to learning motivation, learning readiness and student's self-efficacy in participating in live online learning during the coronavirus outbreak, taking into account gender differences and differences among sub-degree (SD), undergraduate (UG) and postgraduate (PG) students. Technology readiness was used instead of conventional online/internet self-efficacy to determine students' live online learning readiness. The hypothetical model was validated using confirmatory factor analysis (CFA). The results revealed no statistically significant differences between males and females. On the other hand, the mean scores for PG students were higher than for UG and SD students based on the post hoc test. We argue that during the coronavirus outbreak, gender differences were reduced because students are forced to learn more initiatively. We also suggest that students studying at a higher education degree level may have higher expectations of their academic achievement and were significantly different in their online learning readiness. This study has important implications for educators in implementing live online learning, particularly for the design of teaching contexts for students from different educational levels. More virtual activities should be considered to enhance the motivation for students undertaking lower-level degrees, and encouragement of student-to-student interactions can be considered.

Digital competence in higher education research: A systematic literature review

Abstract: In the information and knowledge society, where technology develops rapidly and penetrates deeply into our lives, the discussion about digital competence has become a hot topic today. After the emergence of the Coronavirus (Covid-19) and with its huge impact on the education industry, the concern about digital competence has reached a new height. This systematic literature review uses Web of science and Scopus as databases to store and analyze the existing research on digital competence in higher education settings. The purpose of this review is to provide the scholar community with a current overview of digital competence research from 2015 to 2021 in the context of higher education regarding the definition of digital competence, dimensions used to evaluate digital competence, research purposes, methodologies, and results and limitations. Major findings include that the majority of publications cited both research and EU policy in describing the definition of digital competence. The review indicates that most university students and teachers have a basic level of digital competence. Besides, the institutions of higher education are encouraged to focus on the development students and teachers’ digital competence, create relevant learning strategies and use appropriate tools to improve the quality of education.

Mapping computational thinking through programming in K-12 education: A conceptual model based on a systematic literature Review

Abstract: Computational Thinking (CT) through programming attracts increased attention as it is considered an ideal medium for the development of 21st century skills. This intense attention leads to K-12 initiatives around the world and a rapid increase in relevant research studies. However, studies show challenges in CT research and educational practice. In addition, the domain has not been mapped to facilitate comprehensive understanding of the domain challenges and development of CT curricula. The purpose of this study is to develop a conceptual model based on a systematic literature review that maps the CT through programming in K-12 education domain. The proposed Computational Thinking through Programming in K-12 education (CTPK-12) conceptual model emerges from the synthesis of 101 studies and the identification of CT Areas. The proposed model consists of six CT Areas (namely Knowledge Base, Learning Strategies, Assessment, Tools, Factors and Capacity Building) and their relationships. The model could aid domain understanding and serve as a basis for future research studies. In addition, it could support the integration of CT into K-12 educational practices, providing evidence to educational stakeholders and researchers as well as bringing closer research, practice and policy.

The effectiveness of partial pair programming on elementary school students’ Computational Thinking skills and self-efficacy

Abstract: Computational thinking (CT) skills are becoming essential in all aspects of work and life, and CT has become part of the K-12 curriculum around the world. Yet, more research is needed to better understand how to help elementary school students acquire CT skills effectively. The purpose of this study was to examine the effectiveness of partial pair programming (PPP) on elementary school students' CT skills and self-efficacy (SE). The study included four 4th grade classes, with a total of 171 students, who were taking the course entitled “Computational Thinking with Scratch” with the same teacher for one semester. Two classes (84 students) were in the Experimental Group (EG, 44 boys and 40 girls) while two other classes (87 students) were in the Control Group (CG, 45 boys and 42 girls). The students in the EG were paired up for the programming assignments while the students in the CG did the assignments on their own. The results showed that the students in the EG improved their CT skills and SE more significantly than those in the CG group. There was a low correlation between CT and SE in the post-test of both groups. The interviews with the teacher and the students afterwards provided insights in understanding the results. The findings suggest that in K-12 programming teachers could use PPP as an effective approach to improve students’ CT skills, programming SE, and beyond.

Individual motivation and social media influence on student knowledge sharing and learning performance: Evidence from an emerging economy

Abstract: Social media has become a useful tool for learning and teaching due to its functions for knowledge sharing, such as documents exchange, virtual communication, and knowledge formation. Higher education institutions (HEIs) that recognise the value of social media and the importance of individual motivation have sought to encourage its use to bolster learning performance. Using social cognitive theory and connectivism theory, we developed a model that theorises the influence of social media and individual motivation (reputation and altruism) on knowledge sharing and learning performance among students in higher education. To test the model, we employed covariance-based structural equation modelling (CB SEM) on survey data that was collected using questionnaires from 407 students enrolled in the top 10 private universities in West Malaysia. Congruently, we established the utility of the Heterotrait-Monotrait (HTMT) ratio (which was traditionally confined to variance-based or partial least squares SEM) as a discriminant validity measure for CB SEM. As a result, our study empirically evidences that social media functions (documents exchange, virtual communication, and knowledge formation) and individual motivation (reputation) are core factors that HEIs can leverage to encourage knowledge sharing and improve learning performance among tertiary students. The paper concludes with a discussion of its implications, limitations, and future research directions.

Effects of a social regulation-based online learning framework on students’ learning achievements and behaviors in mathematics

Abstract: Most university degrees often require students to demonstrate proficiency in mathematics, which is the basic requirement in many fields, such as science, engineering, or technology. Mathematical knowledge is so common as to be essential in higher education. Although mathematical skills are crucial to the success of study in many domains, a large number of students are not willing to study related courses. Anxiety and pressure triggered by previous failures in mathematic learning are considered as the reason. The online learning environment provides students with opportunities to exchange opinions with others and facilitate their self-regulated learning. Scholars believe that the learning performances of students can be enhanced if they make reference to other students' learning strategies during the study process. The practice of making references to other students' learning strategies and mutually monitoring each other during the study process is called social regulation. The study efficiency of social regulation in learning mathematics will need to be verified. This study has adopted a social regulation-based online learning approach for assisting students in achieving learning goals with peers' power. At the same time, this study conducted an experiment with an experimental group and a control group. The social regulation-based online learning approach was used by the experimental group while the conventional self-regulated learning approach was used by the control group. According to the results, the social regulation-based online learning approach enhances students' learning achievements and learning motivations in mathematics. Based on the results of the sequential pattern analysis for investigating the online learning behaviors of the two groups of students, students who use the social regulation-based online learning approach have more positive online learning behaviors, such as reading the supplementary materials regarding the wrongly answered questions and revising the notes. On the contrary, students who use the conventional self-regulated learning approach only pay attention to the results of tests and feedback provided by their teacher. They seldom have behaviors of looking at the supplementary materials, adding or deleting notes. With the above verification, the developed system of this study not only enhances students’ learning performances, but also guides them to have more meaningful learning behaviors in mathematics.

The relation between in-service teachers' digital competence and personal and contextual factors: What matters most?

Abstract: The objective of this article is twofold: (i) to provide a valid and reliable instrument to measure teachers' digital competence on the basis of the European Framework for the Digital Competence of Educators (also referred to as DigCompEdu) and (ii) to examine the relation between in-service teachers' digital competence and personal and contextual factors. For this purpose, a study was conducted with 1071 in-service teachers. The instrument was validated with respect to its factorial structure, and the relation between teachers' digital competence and personal and contextual factors was analysed using three different analyses: (i) simple linear regression, (ii) multiple linear regression, and (iii) machine learning. The results show that all the analyses conducted confirm the prevalence of personal factors over contextual ones, as well as their stronger predictive capacity. Gender and age differences were found, but the number of tools used for teaching and learning was the strongest predictor of teachers' digital competence, followed by ease of use, confidence in using digital technology, and openness to new technology. The article shows the soundness of the DigCompEdu framework and provides knowledge that could benefit teacher training programmes and inform policy and practice.

Same benefits, different communication patterns: Comparing Children's reading with a conversational agent vs. a human partner

Abstract: Storybook reading accompanied by adult-guided conversation provides a stimulating context for children's language development. Conversational agents powered by artificial intelligence, such as smart speakers, are prevalent in children's homes and have the potential to engage children in storybook reading as language partners. However, little research has explored the effectiveness of using conversational agents to support children's language development. This study examined how an automated conversational agent can read stories to children via a smart speaker while asking questions and providing contingent feedback. Using a randomized experiment among 90 children aged three to six years, this study compared these children's story comprehension and verbal engagement in storybook reading with a conversational agent versus an adult. The conversational agent's guided conversation was found to be as supportive in improving children's story comprehension as that provided by an adult language partner. At the same time, this study uncovered a number of differences in children's verbal engagement when interacting with a conversational agent versus with an adult. Specifically, children who read with the conversational agent responded to questions with better intelligibility, whereas those who read with an adult responded to questions with higher productivity, lexical diversity, and topical relevance. And the two groups responded to questions with a similar level of accuracy. In addition, questions requiring high cognitive demand amplified the differences in of verbal engagement between the conversational agent and adult partner. The study offers important implications for developing and researching conversational agent systems to support children's language development.

Assessment of cognitive, behavioral, and affective learning outcomes in massive open online courses: A systematic literature review

Abstract: This systematic review on massive open online courses (MOOCs) in higher education examined the research on the assessment of learning outcomes based on 65 peer-reviewed articles published between 2017 and 2019. This study aims to investigate the learning outcomes, related instruments, and assessment characteristics of these instruments in MOOCs. Learning outcomes that were examined in the studies that were reviewed concerned cognitive, behavioral, and affective learning outcomes. Twenty-five types of assessment approaches were employed to examine these outcomes and to identify the assessment characteristics. The results indicate that a consideration of the assessment of learning outcomes at the beginning of course design could support the formulation of explicit assessment goals and, in this way, instruct learners to work toward learning outcomes. A combination of knowledge tests and skill tasks can be used to examine cognitive outcomes in a particular MOOC. Outcome-oriented feedback rubrics are beneficial to support learner essay performance and interpretations of the utilization of rubrics could better guide providers to give peer feedback. A variety of behavioral and affective outcomes reflect multiple aspects of participant learning in MOOCs, which might contribute to better understanding by teachers and the provision of learning support. Furthermore, assessment tasks throughout the course may differ in difficulty and complexity, which could align with different levels of learner motivation. The findings provide a holistic picture of learning outcomes and related assessment instruments in current MOOCs. Curriculum designers and teachers could benefit from this study to consider appropriate learning outcome variables and instruments to apply in their MOOC practices. Future research might investigate the motivation of learners to participate in a MOOC and how this changes during a MOOC. This could help MOOC designers and teachers to align how learners are motivated, what they want to learn, and what they actually do learn.

Can digital technologies improve students’ efficiency? Exploring the role of Virtual Learning Environment and Social Media use in Higher Education

Abstract: Digital technologies, including Virtual Learning Environment (VL) and Social Media (SM), are well adopted in the Higher Education (HE) setting, yet little is known about the role these tools play in supporting students' achievement of HE goals. This research is the first to examine student efficiency by uncovering the direct links between HE inputs and outputs in consideration of technology use. Building on service productivity theory, a two-phase approach is adopted to empirically examine if VL and SM use enhances students' efficiency in HE goals attainment. The first phase identified a range of HE inputs and outputs perceived by HE students via structured interviews. Through questionnaires, the second phase revealed how technology use changed the input-output transformation. Our findings suggest that students are better off without relying on digital technologies. While VL can enhance students' HE goals achievement with additional inputs, students who use SM are the least efficient. This encourages further work to devise more diligent use of VL and SM under the HE setting.

Immersive virtual reality as a tool to learn problem-solving skills

Abstract: Immersive virtual reality (IVR) technology has demonstrated positive educational outcomes related to its use and is gaining traction in educational and training settings; IVR is expected to have widespread adoption within the classroom in the upcoming years. However, the educational potential of IVR with children has not been thoroughly investigated, especially as a tool for problem-solving skills. Therefore, this study was designed to answer the following questions: (1) Is IVR a useful tool to learn and practice problem-solving skills? More specifically, do children using IVR solve a game better than those using a tablet application or a board game? (2) Does IVR provide a more engaging experience for children to practice problem-solving skills than on a tablet or a board game? (3) Do problem-solving skills learned with IVR technology transfer to real-life (physical game)? Children (n = 120) aged 7–9.9 years were randomly assigned to a problem-solving game in one of three conditions: board game, tablet, or IVR. The results showed that, overall, the percentage of children who completed the problem-solving game was higher in the IVR condition (77.5%), compared with those in the tablet (32.5%) or board game (30%) conditions. We also found that the interest and enjoyment scores of participants using IVR were significantly higher than participants in the other two conditions, and that the children in the IVR condition were able to learn how to solve the problem and transfer their learning to the physical game. IVR is a technology capable of engaging interest and motivating the user, as well as having the potential to assist in cognitive processing and knowledge transfer.

Massive LMS log data analysis for the early prediction of course-agnostic student performance

Abstract: The early prediction of students' performance is a valuable resource to improve their learning. If we are able to detect at-risk students in the initial stages of the course, we will have more time to improve their performance. Likewise, excellent students could be motivated with customized additional activities. This is why there are research works aimed to early detect students’ performance. Some of them try to achieve it with the analysis of LMS log files, which store information about student interaction with the LMS. Many works create predictive models with the log files generated for the whole course, but those models are not useful for early prediction because the actual log information used for predicting is different to the one used to train the models. Other works do create predictive models with the log information retrieved at the early stages of courses, but they are just focused on a particular type of course. In this work, we use machine learning to create models for the early prediction of students' performance in solving LMS assignments, by just analyzing the LMS log files generated up to the moment of prediction. Moreover, our models are course agnostic, because the datasets are created with all the University of Oviedo1 courses for one academic year. We predict students' performance at 10%, 25%, 33% and 50% of the course length. Our objective is not to predict the exact student's mark in LMS assignments, but to detect at-risk, fail and excellent students in the early stages of the course. That is why we create different classification models for each of those three student groups. Decision tree, nave Bayes, logistic regression, multilayer perceptron (MLP) neural network, and support vector machine models are created and evaluated. Accuracies of all the models grow as the moment of prediction increases. Although all the algorithms but nave Bayes show accuracy differences lower than 5%, MLP obtains the best performance: from 80.1% accuracy when 10% of the course has been delivered to 90.1% when half of it has taken place. We also discuss the LMS log entries that most influence the students' performance. By using a clustering algorithm, we detect six different clusters of students regarding their interaction with the LMS. Analyzing the interaction patterns of each cluster, we find that those patterns are repeated in all the early stages of the course. Finally, we show how four out of those six student-LMS interaction patterns have a strong correlation with students' performance.

A review of automated feedback systems for learners: Classification framework, challenges and opportunities

Abstract: Teacher feedback provided to learners in real-time is a crucial factor for their knowledge and skills acquisition. However, providing real-time feedback at an individual level is often infeasible, considering limited teaching resources. Fortunately, recent technological advancements have allowed for developing of various computer tutoring systems, which can support learners at any place and time by generating personalized feedback automatically. Such systems have emerged in various domains, tackle different educational tasks, and often are designed in very distinctive ways. Consequently, the knowledge in the field of automated feedback systems is rather scattered across different domains and applications, as we illustrate in this study. This paper aims to outline the state-of-the-art of recently developed systems for delivering automated feedback, and thus serves as a source of systematic information for educators, researchers in the educational domain and system developers. More specifically, the contribution of this study is twofold. Firstly, we offer an extensive literature review of the field. As a result of a rigorous selection process, consisting of 4 phases, a total of 109 automated feedback systems is selected for a detailed review and thoroughly classified against numerous dimensions. Secondly, based on a detailed analysis of the recent literature sources and following the design science research approach, a classification framework for automated feedback systems is developed. This framework is used to classify the selected systems, and thus give a detailed overview of the predominantly available educational technologies, the educational settings in which they are applied, the properties of automated feedback they deliver, and the approaches for their design and evaluation. Based on this analysis, several important observations and recommendations are put forward as an outcome of the study. In particular, our study outlines the current fragmentation of the field, discusses a need for a common reference framework, and calls for more personalized, data-driven and student-centered solutions to exploit a larger set of opportunities offered in this age of data.

Successful design and delivery of online professional development for teachers: A systematic review of the literature

Abstract: The growth in online professional development opportunities for teachers, due to the COVID-19 pandemic, prompts us to question what the most effective practices of facilitating professional development online are and what design elements of online professional development (OPD) programs improve teachers' content and pedagogical content knowledge (PCK). These questions are critical to the successful design and delivery of OPD for teachers. To date, there is no systematic review that provides answers to these questions. Hence, this review presents a synthesis of 11 studies that systematically examine experimental and observational studies that tested or evaluated formal OPD programs for teachers. Eight studies were quantitative and three were mixed methods detailing evidence of teachers' OPD program effectiveness, including design elements, that lead to teachers' improved: content knowledge; PCK; beliefs about teaching; self-efficacy; and instructional practices. Design elements identified included a focus on learner supports, further acquisition or development of PCK, engagement, flexibility, individual difference in learners and learning styles, practical learning activities, reflection, relevance and application of knowledge and skills. The analysis uncovers a primary issue that few available publications of teachers' OPD are strong methodologically. This systematic review's findings report on design elements that lead to effective OPD learning experiences for teachers.

The use of Massive Open Online Courses (MOOCs) in blended learning courses and the functional value perceived by students

Abstract: Massive Open Online Courses (MOOCs) are presented as an option to the traditional model of higher education institutions. MOOCs have been used as part of face-to-face regular university courses as a new form of blended learning (BL), but little is known about the best ways to design effective MOOC-based BL. Besides, studies that assess the intention to continue using MOOCs do not assess their quality and value as perceived by students. This study aims to understand how MOOCs can be better integrated into blended learning. To do so, an exploratory case study was carried out a in MOOC-based BL in the discipline Fundamentals of Administration at a Brazilian university to evaluate three aspects: (1) pedagogical approach/rationale; (2) pedagogical/instructional design for integrating the MOOC into the course; and (3) perceived quality and value by the students. The results show that the MOOC was used as a blended learning method in an introductory course, replacing part of the hours of face-to-face classes, allowing an increase of the number of students per teacher, besides making the discipline more attractive to the students. Results also show that the functional value perceived by the students is favorable, with a score of 4.53 (7-point scale) and is influenced by the perceived quality regarding the MOOC (r = 0.29) and blended learning process (r = 0.22). This study extends previous research by demonstrating two different designs of MOOC-based BL that contribute to the improvement of the pedagogical process, reduce costs, and improve the quality problems of MOOCs. In addition, this study developed a model that associates perceived quality and perceived value with the intention to continue MOOCs within the context of the MOOC-based BL. This model may be used to evaluate which strategies for MOOC-based BL generate the highest perceived quality by the students.

Learning to code and the acquisition of computational thinking by young children

Abstract: This longitudinal study examined changes in Computational Thinking (CT) skills in first and second grade students exposed to a developmentally appropriate coding curriculum. The “Coding as Another Language” (CAL) curriculum spans seven weeks and uses the KIBO robot to engage students in learning that integrates programming and literacy concepts. We compared children receiving CAL (N = 667) to a control group (N = 181) who participated in typical classroom activities without coding (No-CAL). TechCheck, a validated “unplugged” CT assessment suitable for young children regardless of their coding experience, was used to measure CT. Over the course of the study, children who received CAL-KIBO improved on TechCheck (Mchange = 0.94, p

The potential of 360-degree virtual reality videos to teach water-safety skills to children

Abstract: This study investigated the potential of Virtual Reality (VR), using 360-degree (360°) videos, as a tool to teach children about water-safety skills. Children (n = 182) aged 10–12 years were randomly assigned to learn about water safety using one of three instructional mediums: 360° VR videos, traditional video, or poster. The training was designed to address specific themes that contributed to drowning in coastal environments, allowing children to learn about dangers of rip currents in a relatively safe environment. Overall, 95% showed improved knowledge of water safety after participating in the water-safety workshop and retained their knowledge during the subsequent tests both one and eight weeks later. No difference was found in the learning outcomes obtained across the three mediums; however, participants in the 360° VR medium reported higher levels of interest and enjoyment than participants using the other two mediums (91% of students in the 360° VR video group found the activity engaging versus 61% for traditional video and 51% for the poster). Teacher feedback also indicated that 360° VR videos are a useful, engaging, and effective method of learning. Overall, we found support for the hypothesis that 360° VR videos are a useful tool to teach targeted skills, and that using 360° VR videos is more motivating and engaging than using traditional learning methods. We also found evidence to support the hypothesis that 360° VR videos are an effective tool for self-directed learning.

Variability of Teachers’ Technology Integration in the Classroom: A Matter of Utility!

Abstract: Technology integration in the classroom is seen as an important educational innovation to enhance teaching and learning processes in the 21st century Teacher motivation has been seen as a critical prerequisite for successful technology integration in the classroom, particularly in early phases of educational innovation However, whether teacher motivation is a stable versus variable construct in such innovation contexts and how teacher motivation is decisive for effective technology integration are open issues Most previous studies relied on cross-sectional studies and were restricted to quantity measures which only investigated the mere usage of technology but not the quality of technology integration Against this background, we implemented a web-based teacher diary for in-service teachers (N = 18) in the beginning of a government initiative in which classes were equipped with one-to-one technological infrastructure By using a mixed method approach, we found considerable variability of teacher motivation, frequency, and quality of technology integration across lessons over a period of six weeks More importantly, the variability of the quality of technology integration was explained by teachers’ technology-related utility beliefs, as a crucial facet of technology integration and specific factors within the different instructional contexts The findings highlight the role of teacher motivation as well as the particular context in technological educational innovations

Associations between learning analytics dashboard exposure and motivation and self-regulated learning

Abstract: Learning analytics dashboards (LADs) are intended to give relevant information to students and other stakeholders to inform potential next steps in the learning process. The current study examines the relationship between information indirectly presented through academic advisors' use of LADs, and college students' academic motivation, self-regulated learning, and academic achievement. We modeled how changes in student motivation and self-regulated learning (SRL) were related to what occurred during 1-on-1 meetings with academic advisors during which students had the potential to view representations of their achievement embedded within an Early Warning System (EWS) that visually represented aspects of their academic performance referenced with course averages. Constructs associated with SRL were moderated by advisor-advisee meetings. Results indicated that advisors' use of EWS while they met with students was negatively associated with the rate of decrease of students' reporting of using memorizing strategies but positively related when students' performance was compared to that of their peers. We discuss the moderating effects of students’ exposure to visualizations of academic performance on their SRL strategies and academic motivation. This study points to the importance of monitoring the effects of information presented via EWS on motivation and SRL.

University students’ profiles of online learning and their relation to online metacognitive regulation and internet-specific epistemic justification

Abstract: This study examined university students’ online learning profiles in terms of activities, purposes, and engagement, and how the different profiles related to metacognitive regulation and internet-specific epistemic justification. Three questionnaires were used to collect data from 389 undergraduate and graduate students in Thailand. The results indicated five emergent clusters as follows: highly-engaged self-driven online contributors, moderately engaged self-driven online viewers, less engaged self-driven online learners, highly engaged course-driven online learners, and less engaged course-driven online learners. Moreover, the students of the five clusters who demonstrated different online learning profiles showed significant differences in their metacognitive regulation and internet-specific epistemic justification. Implications are discussed.

Learning analytics dashboards for adaptive support in face-to-face collaborative argumentation.

Abstract: Despite the potential of learning analytics for personalized learning, it is seldom used to support collaborative learning particularly in face-to-face (F2F) learning contexts. This study uses learning analytics to develop a dashboard system that provides adaptive support for F2F collaborative argumentation (FCA). This study developed two dashboards for students and instructors, which enabled students to monitor their FCA process through adaptive feedback and helped the instructor provide adaptive support at the right time. The effectiveness of the dashboards was examined in a university class with 88 students (56 females, 32 males) for 4 weeks. The dashboards significantly improved the FCA process and outcomes, encouraging students to actively participate in FCA and create high-quality arguments. Students had a positive attitude toward the dashboard and perceived it as useful and easy to use. These findings indicate the usefulness of learning analytics dashboards in improving collaborative learning through adaptive feedback and support. Suggestions are provided on how to design dashboards for adaptive support in F2F learning contexts using learning analytics.

Determinants of mobile learning acceptance for STEM education in rural areas

Abstract: Science, Technology, Engineering, and Mathematics (STEM) is faced with challenges, resulting in learners' poor performance especially in rural areas. Previous studies have shown that mobile learning can be used to alleviate the challenges faced in STEM education in rural areas. Despite the opportunities that mobile learning can bring to STEM education, very little is known about high school STEM learners', their teachers', and parents' acceptance of mobile learning, particularly in rural settings. This study proposed and used the High School's Acceptance of Mobile Learning Model to investigate the factors that predict rural high school STEM learners', their parents', and teachers' behavioural intention to use mobile learning for STEM learning. The High School's Acceptance of Mobile Learning Model is based on the Technology Acceptance Model (TAM). Stratified random sampling was used to select 550 survey participants. Partial least squares structural equation modeling was used to analyse data from 417 valid questionnaires. The proposed model explained 40.8% of the variance in learners', teachers', and parents' acceptance of mobile learning. The original TAM variables (perceived attitude, perceived usefulness, and perceived ease of use) had direct relationship with behavioural intention, and they also played mediating roles between the external variables and behavioural intention. Multigroup analysis results showed that, for parents and learners, three paths were significantly different. In contrast, all paths were not statistically significant different for learners and teachers. However, all the paths were significant in each group, meaning that High School's Acceptance of Mobile Learning Model can be used to predict acceptance of mobile learning for learners, parents, and teachers.

Predictive effects of undergraduate students’ perceptions of social, cognitive, and teaching presence on affective learning outcomes according to disciplines

Abstract: The Community of Inquiry framework has been used in numerous studies, yet these studies rarely examine disciplinary differences as a potential factor in student outcomes. To address the research gap, this study examined the differences in students' perceived social, cognitive, and teaching presence and their predictive effects on students' affective learning outcomes (perceived learning outcomes and satisfaction) according to their academic disciplines. The survey data were collected from 25 undergraduate online courses at two universities. The participants (n = 418) were recruited from four disciplinary areas: soft-pure (n = 142), soft-applied (n = 63), hard-pure (n = 78), and hard-applied (n = 135). MANOVA and stepwise multiple regression analyses were conducted. The results indicated that there is no significant difference in the levels of students' perceived social, cognitive, and teaching presences, yet it is important to note the trend for all disciplines which was teaching presence was perceived as the highest presence, followed by cognitive and social presence. In addition, differences were found in the predictive effects of each presence on students’ perceived learning outcomes and satisfaction according to their disciplines.

“Think globally, act locally”: A glocal approach to the development of social media literacy

Abstract: Despite the documented number of studies that investigate social media in teaching and learning settings, the topic of social media literacy is still an under-researched area. This study adopts the theoretical lens of New Literacy studies to suggest a combined perspective for investigating social media literacies. This perspective considers both social media skills that are transversal across different social media (global skills), and those that pertain to a specific social media platform (local skills). It examines practices that are decontextualized (literacy as something to be acquired), and those that are situated and context-dependent (literacy through participation). To map current research on social media skills, a systematic literature review was conducted. Analysis of 54 publications was carried out following the UNESCO DLGF framework for digital literacy competencies, and also using a critical lens based on four metaphors whereby, for learning purposes, social media are seen as a tool, as a process, as collaboration, and as participation. The results show that most of the studies consider global social media skills, while only a few examine skills sets specific to a particular social media platform. In addition, most of the identified skills concern decontextualized practices, with very few studies emphasizing the importance of fostering situated social media practices. We conclude that there is a need for more expansive theoretical elaboration in the field, and provide a number of recommendations for investigating, understanding, and designing educational curricula and activities that support the development of social media literacy.

Virtual reality for fire safety training: Influence of immersion and sense of presence on conceptual and procedural acquisition

Abstract: A fire can have serious economic and human consequences. However, in many cases, rapid intervention and appropriate behavior can significantly reduce this threat. For this it is important that people are properly trained. Faced with the economic, ecological and organizational requirements and constraints linked to fire safety training, virtual training environments appear to be a judicious alternative to traditional training. However, before committing companies to invest in expensive devices, it is necessary to ensure the effectiveness of such devices. The literature is rich and divided on this subject, and it appears that certain characteristics of the system and of the learners are decisive. In this context, the objective of our work was to study the effects of immersion, the feeling of presence as well as the interaction between these 2 factors on the performance of conceptual and procedural learning. Certain variables were also controlled such as gender, tendency to immersion, previous experience in computers and video games. Our work shows that immersion promotes procedural but not conceptual learning, and that neither the sense of presence, nor the interaction between immersion and the sense of presence affect these two types of learning in our training task. Apart from the knowledge of fire which potentiates the effect of immersion on procedural learning, the variables considered in our study (computer experience, video game experience and genre) had no impact on performance. Understanding the impact of the technical device or the characteristics of users on conceptual and procedural learning is a major challenge in helping trainers to develop pedagogical devices in order to better exploit the opportunities offered by new technological approaches.

Digital inequality at home. The school as compensatory agent

Abstract: Following the lockdown caused by the COVID-19 crisis, the forced digitization of teaching at all levels of education has highlighted the social problem of digital inequality at home The article addresses this issue by looking at the role of both social background, as measured by socio-economic-status (SES), in this inequality, and that of schools A multidimensional approach to digital inequality is proposed, incorporating the frequency and quality of use of digital media, as well as ICT access To this end, multiple structural equation models are estimated using data from the last PISA cycle (2018), for a total of 161,443 students from 6261 schools and 21 European countries, to check the influence on each of these three dimensions of both the SES and the integration of ICT in schools The results confirm that for most European countries: (1) access to ICT at home is influenced to a greater extent by the family's SES than by the integration of ICT at school; (2) both the frequency and quality of use of ICT at home are influenced more by the integration of ICT at school than by the SES of the family, while in some countries the influence of the social aspect is practically irrelevant Therefore, the integration of ICT in schools emerges as a compensatory measure for the social inequalities of students and may contribute to the reduction of digital inequality

Active learning with online video: The impact of learning context on engagement

Abstract: Learning with online video is pervasive in higher education. Recent research has explored the importance of student engagement when learning with video in online and blended courses. However, little is known about students' goals and intents when engaging with video. Furthermore, there is limited empirical evidence on the impact of learning context on engagement with video, which limits our understanding of how students learn from video. To address this gap, we identify a set of engagement goals for learning with video, and study associated student activity in relation to learning context (course week, exam, and rewatch). In Study 1, we conducted a survey (n = 116) that maps students' video viewing activities to their engagement goals and intents. We identified a variety of engagement goals, specifically Reflect, Flag, Remember, Clarify, Skim, Search, Orient, and Take a break. In Study 2, we analyzed clickstream data generated by 387 students enrolled in three semester-long courses. We examined the impact of learning context on students’ engagement with video. A multilevel model showed different patterns for online and blended courses. Students in the online course showed much more strategic and adaptive use of video. As the semester progressed, students in the online courses performed fewer Reflect and Search. During exam weeks and when rewatching videos, online students performed more Search within the video. The only trend that was found for blended learning students was an increase in Skim with course week. These findings have implications for video players that adapt to context, such as helping students easily locate important in-video information during the exam week or when rewatching previously watched videos.

Understanding learners’ acceptance of high-immersion virtual reality systems: Insights from confirmatory and exploratory PLS-SEM analyses

Abstract: This article reports on a study that investigated user acceptance of a high-immersion virtual reality learning environment to learn English paragraph writing structure. 134 undergraduate university students participated in the study by using a high-immersion virtual reality system combined with an in-house developed virtual reality learning environment program for the purpose of learning paragraph structure. A post-session questionnaire was used to collect data. A partial least squares structural equation modelling (PLS-SEM) analysis was then conducted to test an extended technology acceptance model conceptualized from a priori theoretical deduction and previous empirical findings. The extended model featured the constructs of Imagination, Immersion, and Interaction as exogenous variables with Perceived Ease of Use and Perceived Usefulness in mediating roles leading to the endogenous construct of Behavioral Intention to Use. Results of the confirmatory PLS-SEM analysis revealed inherent problems with the model's application to the high-immersion virtual reality system and program used. Considering these findings, a PLS-SEM exploratory model optimization analysis was conducted which saw the variable of Immersion best relocated to be a predicator for both the Interaction and Imagination constructs. This exploratory model showed superior predictive relevance and improved significance of the relevant construct paths. Based on these results, this paper provides new theoretical reasoning that is in line with these statistical findings, namely that the construct of Immersion is best positioned as a singular external exogenous variable impacting Interaction and Imagination for the high-immersion virtual reality technology acceptance model used in this study.

In-service teachers' conceptions of mobile technology-integrated instruction: Tendency towards student-centered learning

Abstract: Some previous research has illustrated teachers' conceptions and responsibilities in student-centered classes for assisting potent implementation of novel pedagogies. On the other hand, mobile learning has been widely adopted in education in the past decades, and a great deal of previous research has revealed the effects of mobile learning on students' learning. However, few studies have probed teachers' conceptions of mobile technology-integrated instruction. In this study, a total of 25 elementary school teachers in Taiwan were interviewed, and the phenomenographic method was adopted to explore the teachers' conceptions of mobile learning. As a result of the data analysis, seven qualitatively and hierarchically different categories (7-T) of mobile learning were revealed, namely a “Tool,” “Travel,” “Timeliness/Tutor,” a “Toy,” “Tracking,” “Teamwork,” and a “Tutee.” These hierarchical categories represent a spectrum ranging from “teacher-centered” to “student/teacher interaction,” and “student-centered” instructional strategies. Among the 7 categories, 4 (i.e., Toy, Tracking, Teamwork, and Tutee) are considered as student-centered instructional strategies, and the tracking category had the maximum frequency of teachers’ main conceptions of mobile learning. Thus, mobile technology offers opportunities to facilitate student-centered learning. The results provide educators and teachers with deep comprehension of advanced technology-enhanced learning for designing student-centered learning activities.

The influence of technology acceptance, academic self-efficacy, and gender on academic achievement through online tutoring

Abstract: The study focused on variables which were posited to capture undergraduate students' experiences with a large-scale online tutoring service, and relationships with the students’ perceptions of their academic capabilities and academic performance. A theoretical model incorporating variables from research on Technology Acceptance and Social Cognitive Theory was developed and tested. A total of 365 undergraduate students from a university located in Sydney, Australia, completed an online survey. Data were analysed using confirmatory factor analysis (CFA) and structural equation modeling (SEM), and multi-group analyses (MGA). The measurement model demonstrated configural, metric and scalar invariance. There were differences between males and females regarding latent means, with females scoring higher than males for facilitating conditions. The regression paths were consistent across males and females (i.e., invariant) in the full structural model. Facilitating conditions was positively associated with the perceived usefulness of technology, which in turn was positively associated with academic self-efficacy. Surprisingly, perceived ease of use did not have a statistically significant association with perceived usefulness. Academic self-efficacy was positively associated with academic achievement. Implications, particularly for online tutoring service providers, are discussed.