Education and Information Technologies

MOOCs might be an important organization way to realize the online learning process. Online technology and sharing technology enable MOOCs to realize the adaptive scheduling of learning resources, as well as the independent construction of learning sequences. At the same time, it also generates a large number of complex learning behaviors. How to mine and predict the value and laws of MOOCs is a difficult problem in learning analytics applied to MOOCs. This study integrates the context information of the learning process of MOOCs, designs a deep learning model based on multi-entity knowledge graph, in order to predict and track the interest propagation of learning behaviors, and realizes the learning trend guidance mechanism supported by multi features and complex relationships. Through sufficient experiments, the effectiveness and reliability of this model are verified, and based on the analysis results, the best path and implementable scheme for the interest propagation of learning behaviors are constructed. The whole research might provide more references for the study of learning behaviors described by multi-entity knowledge graph of MOOCs.

The online and offline blended learning mode based on SPOC has gradually become a popular teaching mode in higher institutions due to COVID-19 pandemic. However, students of English as a Foreign Language (EFL) in SPOC-based blended learning environments continue facing problems of low participation and persistent intention. In order to explore the influencing factors of EFL students’ continuance intentions to learn under the SPOC blended learning environment, this study recruits 48 EFL students from three higher vocational colleges based on the grounded theory. Through the triple coding method of open, axis, and selective coding based on the grounded theory and the used of software Nvivo to conduct a triple coding analysis of the text data obtained from the in-depth interviews and focus group interviews, a theoretical model of the influencing factors of EFL students’ continuous learning intention (pre-influencing factors, external situational factors, and continuance intention) is proposed. Besides, a systematic framework based on stakeholders response to improve EFL students’ continuance learning intentions in SPOC-based blended learning environments is constructed accordingly. This study can provide reference for basic theory and variable selection for subsequent research on the influencing factors of EFL students’ continuance learning intentions in China and elsewhere.

In recent years, an increasing number of teachers and researchers have used virtual reality (VR) to enhance English as a foreign language (EFL) learning, but the learning effects they found varied. Because of these differences, we conducted a meta-analysis. This study aims to compare the effectiveness of VR-based EFL learning methods with traditional EFL learning methods, and to determine what factors led to these results. We searched for articles published from 2015 to 2021 using Web of Science, ERIC, and Google Scholar. A total of 23 randomized controlled trials (RCTs) or quasi-experimental studies were included, and the effect size (ES) was calculated. The results show that the VR-based EFL learning method is significantly better than the traditional EFL learning method and has a small positive effect (g = .445). We also coded the characteristics of the samples to examine their moderating effect on the results. We found that educational levels, country/area, and EFL learning outcomes have significant differences that can explain the variance in ES among the samples. According to the analysis results, we also provide suggestions on which learning outcomes are most helpful, how to choose the best educational stages, learning materials, and type of VR to promote EFL learning performance, and directions for future research and practice.

Leadership is one of the skills necessary for the career of future health professionals. The purpose of this study is to get an insight into developing leadership skills in online learning as well as ways to deal with various management issues. The methods used in this study include a survey, quantitative and qualitative analysis, and statistical data processing. The research conducted among medical students suggests that a leader is identified by behavioral, cognitive personality traits, and physical qualities. Online learning creates an inclusive environment, as well as directly prepares the ground for gaining leadership. Such format of learning reduces society’s pressure regarding the molding of personality. The implications of the study are based on the development of tools for addressing leadership and management issues in online learning. It aims to demonstrate the benefits of online learning and show facets of leadership that are worth paying attention to.

Digital advances in the learning space have changed the contours of student engagement as well as how it is measured. Learning management systems and other learning technologies now provide information about student behaviors with course materials in the form of learning analytics. In the context of a large, integrated and interdisciplinary Core curriculum course in a graduate school of public health, this study undertook a pilot randomized controlled trial testing the effect of providing a “behavioral nudge” in the form of digital images containing specific information derived from learning analytics about past student behaviors and performance. The study found that student engagement varied significantly from week to week, but nudges linking coursework completion to assessment grade performance did not significantly change student engagement. While the a priori hypotheses of this pilot trial were not upheld, this study yielded significant findings that can guide future efforts to increase student engagement. Future work should include a robust qualitative assessment of student motivations, testing of nudges that tap into these motivations and a richer examination of student learning behaviors over time using stochastic analyses of data from the learning management system.

This study explored the interaction between cognition and emotion in blended collaborative learning. The participants (n = 30) of this study were undergraduate students enrolled in a 16-week course on information technology teaching. These students were divided into six groups of five people each. The behavior modes of the participants were analyzed using a heuristic mining algorithm and inductive miner algorithm. Compared with the groups with low task scores, the high-scoring groups exhibited more reflection phases and cycles in the interaction process and thus more frequent self-evaluation and regulation behavior for forethought and performance. Moreover, the frequency of emotion events unrelated with cognition was higher for the high-scoring groups than for the low-scoring groups. On the basis of the research results, this paper presents suggestions for developing online and offline blended courses.

This study highlights the importance of educational leaders’ responsibilities in virtual spaces, as they are perceived by school faculties and provides a validated tool to measure teachers' perception of a "principal's leadership presence in social media networks". 235 Israeli teachers participated in the study –180 (77%) females and 55 (23%) males, using a questionnaire consisting of 14 items scaled in a 6-point Likert format. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) reveal four modalities of the principal’s on-going leadership presence in social media networks: branding and communicative, transformational, supportive-protective and enforcement presence. The questionnaire may provide principals and educational policy designers with a plan to regulate the socio-professional relationship among a school's stakeholders.

Gamified learning is an instructional strategy that motivates students to learn, and the use of multiple representations assists learning by promoting students’ thinking and advanced mathematical problem-solving skills. In particular, emergency distance learning caused by the COVID-19 pandemic may result in a lack of motivation and effectiveness in learning. This study designed an online gamified learning activity incorporating multi-representational scaffolding and compared the differences in the learning achievement and motivation for the gamified activity and general synchronous distance learning. In addition, for the group that conducted the gamified learning activity, we measured the participants’ flow, anxiety, and emotion during the activity. A total of 36 high school students participated in the experiment. The results indicated that the gamified learning activity was not significantly effective in terms of enhancing learning achievement. In terms of learning motivation, a significant decrease in motivation was found for the group using general synchronous learning, while a significant increase in motivation was found for the group using synchronous gamified learning. This indicates that despite the negative impact of the pandemic on learning, gamified learning still enhances students’ learning motivation. The results of flow, anxiety, and emotion showed that the participants had a positive and engaged experience. Participants provided feedback that the multi-representational scaffolding facilitates learning.

The purpose of this study is to explore attributes that influence the quality of smart classrooms from the perspective of higher education teachers. Relying on a purposive sample of 31 academicians from Gulf Cooperation Council (GCC) countries, the study identifies themes related to quality attributes of technology platforms and social interactions. These attributes are user security, educational intelligence, technology accessibility, system diversity, system interconnectivity, system simplicity, system sensitivity, system adaptability and platform affordability. The study identifies management procedures, educational policies, and administrative practices that enact, engineer, enable, and enhance these attributes in smart classrooms. The findings also highlight strategy-oriented planning and cause-driven transformation as the main smart classroom contexts influencing the quality of education among interviewees. With insights from the interviews, this article discusses some theoretical and practical implications of the study, research limitations, and potential future research directions.

Cyberbullying has generated interest for researchers in the field of psychology and education in recent years. While most studies have focused on samples of adolescents, the university environment also deserves special attention due to its serious consequences on students. It is therefore very important to prevent cyberbullying in the context of university. The objectives of this study were to identify different profiles regarding cyberbullying and cybervictimization behaviors and examine the relationship between cyberbullying, social anxiety, and aggressiveness. A total of 1,368 university students participated in the study by completing the European Bullying Intervention Project Questionnaire (EBIPQ), the Social Anxiety Questionnaire for Adults (CASO-A30), and the Aggression Questionnaire (AQ). The latent profile analysis identified three cyberbullying profiles: a first group with low scores in cyberaggression and cybervictimization (not involved; 87.6%), a second group with moderately high scores in cyberaggression and cybervictimization (victimized cyberbullies; 10%), and a third group with high scores in cybervictimization and very high scores in cyberaggression (cyberbullies; 2.4%). The profile of “victimized cyberbullies” students presents higher scores in physical, verbal, anger, and hostility than the group of “not involved” students, while no differences in social anxiety were found between the groups analysed. Cyberbullying preventive programs should focus on the management of aggressive behaviors for those who have moderate scores in cybervictimization and cyberbullying behaviors, and social anxiety may not be differentiated between cyberbullying groups at this academic stage.

This paper proposes to evaluate learning efficiency by implementing the flipped classroom and automatic source code evaluation based on the Kirkpatrick evaluation model in students of CS1 programming course. The experimentation was conducted with 82 students from two CS1 courses; an experimental group (EG = 56) and a control group (CG = 26). Each student in each group completed 15 programming tasks. The level of knowledge of the participants acquired between the two groups is measured using the Kirkpatrick model, taking as a source a pre-test of previous knowledge, the grade assessment, the time of the activities, and a post-test of learning achieved. When comparing the submits time between the experimental and control group, it is observed that the value of the means is similar for the EG and CG; in this case, time is not a factor for comparison between the groups. However, in the grading, the value of the means is different for the EG and CG; EG students scored better than CG students. The evaluation of the Kirkpatrick model shows that the strategy implemented, on the one hand, does not improve the time of the activities; on the other hand, it improves the grades in the CS1 course.

This study investigated the extent to which self-report and digital-trace measures of students’ self-regulated learning in blended course designs align with each other amongst 145 first-year computer science students in a blended “computer systems” course. A self-reported Motivated Strategies for Learning Questionnaire was used to measure students’ self-efficacy, intrinsic motivation, test anxiety, and use of self-regulated learning strategies. Frequencies of interactions with six different online learning activities were digital-trace measures of students’ online learning interactions. Students’ course marks were used to represent their academic performance. SPSS 28 was used to analyse the data. A hierarchical cluster analysis using self-reported measures categorized students as better or poorer self-regulated learners; whereas a hierarchical cluster analysis using digital-trace measures clustered students as more active or less active online learners. One-way ANOVAs showed that: 1) better self-regulated learners had higher frequencies of interactions with three out of six online learning activities than poorer self-regulated learners. 2) More active online learners reported higher self-efficacy, higher intrinsic motivation, and more frequent use of positive self-regulated learning strategies, than less active online learners. Furthermore, a cross-tabulation showed significant (p < .01) but weak association between student clusters identified by self-reported and digital-trace measures, demonstrating self-reported and digital-trace descriptions of students’ self-regulated learning experiences were consistent to a limited extent. To help poorer self-regulated learners improve their learning experiences in blended course designs, teachers may invite better self-regulated learners to share how they approach learning in class.

Data-driven learning (DDL) has been demonstrated to be an operative strategy for assisting learners to handle a range of writing-related problems. Several studies have been conducted to compare the pedagogical effectiveness of DDL in English as a foreign language (EFL) writing. However, only a few studies have identified key factors that may affect learning outcomes when designing DDL activities. To bridge this gap, the present study looked at the medium-term effects of DDL activities in EFL writing. A pre-post quasi-experimental research design and semi-structural interviews were arranged to collect data from 64 Arab EFL undergraduate students. The DDL was carried out with the aid of BNCweb and offered the assessment of the findings by contrasting the efficiency of BNCweb with that of Sketch Engine, which is employed as a reference tool by EFL learners. The quantitative results showed that the experimental group’s use of BNCweb inspired their writing to be more fluid and consistent in the posttest as compared to the control group, which employed the Sketch Engine tool. However, no significant difference was detected between the groups in writing intricacy. The qualitative results indicated that students had positive attitudes toward using BNCweb, despite the challenges of implementing corpora in the writing process. It was recommended that integrating corpora with other types of reference sources would be a viable solution to overcome any potential obstacles for EFL learners.

Plagiarism has been among the top forms of academic misconduct. Detective, reactive and proactive measures are taken to mitigate plagiarism in scholarly works. Text-matching tools play a significant role in the detection of plagiarism. Many studies have tested the performance of text-matching tools in detecting plagiarism from various perspectives. However, no study addressed the performance of such tools in ideographic languages, particularly Japanese. Considering the sharp increase in the number of academic Japanese text and plagiarism incidents in the Japanese context, it is essential to explore to what extent text-matching tools catch similarities in Japanese texts and respond to the needs of Japanese users. Within this scope, this study set out to explore the coverage and usability performance of text-matching tools in the Japanese language. We tested the coverage performance of 10 text-matching tools with five types of intentionally plagiarized documents. Also, we tested the usability performance via a feature checklist. The testing results suggested that the tools generally give a relatively higher performance on the usability side rather than the coverage aspect. Most tools have minimal coverage performance in the Japanese language. In the end, we provided takeaways for vendors, policymakers and educators.

When the traditional "one size fits all" approach is used in designing educational games, the game context is usually arranged in a fixed sequence. However, the designated content may not effectively support the diversity of players. The player's ability and characteristics should be considered and supported with an appropriate learning context embedded in the game to facilitate personalised experiences. Adapting game scenarios to a player's characteristics can boost motivation and ultimately improve learning outcomes. This research applies a context-aware design approach and the Learner-Centered Design approach to establish a personalised adaptation framework for designing educational serious games and enhancing personalised knowledge delivery. The proposed framework decouples the game logic implementation and adaptation mechanism. It dynamically adapts the designed game objects and activities to personal learning objectives, learning levels and learning progress to achieve a non-linear learning sequence. Through synchronous real-time xAPI message exchange mechanisms, system components and learning content adaptation are enabled. The adaptation aims to fit personal learning objectives and provide a non-linear learning sequence in a game environment. The framework provides students with personalised learning experiences. A game named GhostCoder is implemented and used to evaluate the framework. Based on the externalised adaptive mechanism, the game content is adapted to the player's performance by adjusting the difficulty of the learning content within the game. Testing of the game in the lab environment has been performed. At the next stage, an evaluation will be conducted with the target groups of students.

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

This study explored the relationships among regulated learning, teaching presence and student engagement in blended learning. A two-level model was designed based on contextual factors (teaching presence) and individual factors (regulated learning), and experience sampling method was employed to collect intensive longitudinal data on 139 participants across three universities over 13 weeks in a blended course. Furthermore, multilevel regression analysis were conducted to examine the effects of teaching presence, self-regulated learning (SRL), co-regulated learning (CoRL) on intra- and interindividual variance in student engagement. The findings were as follows. 1) Perceived teacher support and instructional design fit had a significant positive effect on cognitive and emotional engagement and were crucial contextual factors that influenced intraindividual variance in learning engagement. 2) SRL and CoRL were copredictors of student engagement in blended learning. CoRL was more related to emotional engagement, while SRL was more related to cognitive engagement. 3) Modality had a significant effect on cognitive engagement but not on emotional engagement. 4) SRL and CoRL positively moderated the relationship between perceived teaching presence and cognitive engagement, while they negatively moderated the relationship between teacher support and emotional engagement, i.e., the relation between teacher support and emotional engagement was stronger in situations of low SRL or CoRL. Implications for teaching practice on blended learning were also discussed.

This study explores the effects of pre-service teachers’ digital literacy and self-efficacy on their perception of AI education for young children in early childhood education settings. Digital literacy refers to the ability to communicate with others by using digital technology, including the ability for sharing knowledge and information after user’s creation. A survey was conducted on 212 pre-service early childhood teachers at two Universities located in the eastern United States, and the collected data were analyzed by descriptive statistics, correlation analysis, and hierarchical multiple regression. As a result of the study, first, pre-service teachers had high critical thinking among the sub-factors of digital literacy, but relatively low problem-solving skills. Second, the relationship between digital literacy, self-efficacy, and the perception of AI education for young children showed a positive correlation. Third, among the sub-factors of digital literacy of pre-service early childhood teachers, technical application, learning interaction, and problem-solving with teachers’ self-efficacy were found to have a significant effect on the perception of AI education for young children. This study proposes that developing a pre-service teacher education program that can improve their digital literacy and self-efficacy is necessary for guiding early childhood teachers to use artificial intelligence technology with young children in early childhood education classrooms in educationally meaningful ways.

With the rapid development of Artificial Intelligence, automatic writing evaluation (AWE) has received much attention from English Foreign Language (EFL) writing teachers. However, the obstacles and potential problems of integrating AWE in EFL writing instruction have yet to be explored. Scholars have indicated that the effectiveness of AWE in EFL writing instruction depends on the learners' depth of reflection. Hence, this study proposes a learning approach that integrates AWE and peer assessment (PA) based on the knowledge-building theory, with the expectation that learners will be able to strengthen their reflections on AWE feedback through PA, and thereby improve their EFL writing performance. To examine the effectiveness of the proposed approach, a quasi-experiment was conducted in a university EFL writing class. One of the classes (33 students) was the experimental group using the PA-AWE approach, and the other class (31 students) was a control group that studied using the conventional AWE approach (C-AWE approach). Findings revealed that the PA-AWE group outperformed the C-AWE group regarding EFL writing performance, learning motivation, critical thinking, and reduced EFL writing anxiety. In addition, a thematic inductive qualitative analysis of the interview data indicated each approach's benefits and learning conceptions.

This paper examines the invisible barrier that can challenge teachers when teaching online, called the fourth wall. Using a presence framework derived from the literature, we explored how experienced teachers manage the absence of visual cues and identify the pedagogical practices they adopted as a response. Data from semi-structured interviews with 22 teachers experienced in online teaching was analysed for individual presence, place presence, and co-presence. Results indicate seven different types of individual presence, four different types of place presence, and three different types of co-presence. Overall, findings show that teachers discussed developing students' individual connections to the online lesson more often compared with developing co-presence (student-to-student engagement) with place presence being representative of the online learning space. Specific strategies that teachers used to support each presence are presented and implications are provided for how this affects the move to an increased use of blended and online learning in the schooling context.

The unanticipated switch from face-to-face learning to online education caused by the Covid-19 pandemic has led to a lack of familiarization preparation for students, potentially hampering their learning processes in several ways. The success of online learning is primarily based on the quality of the information systems, self-regulated learning, and intrinsic learning motivation. The severe stress amid epidemic lockdowns might trigger negative impacts on students’ learning motivation and self-regulated learning. Nevertheless, studies examining the relationship between information system success, self-regulated learning, perceived stress, and intrinsic learning motivation in the context of developing countries are still scarce. The current research aims to address this gap in the literature. Participants were 303 university students. The results of second-order structural equation modelling revealed the positive direct and indirect relationships between information system success, intrinsic learning motivation, and online self-regulated learning. Besides, despite the insignificant relationships between perceived stress, intrinsic learning motivation, and online self-regulated learning, most participants in this study were found to have moderate to high stress levels. Hence, the potential adverse effect of stress on students’ learning process should not be ignored. The results provide implications for educators and researchers studying online learning environments and educational psychology.

The purpose of this study was to develop an invention instruction program based on the Theory of Inventive Problem Solving (TRIZ) for preservice invention teachers and test the effects of the program on teachers’ creativity beliefs, creativity, and invention teaching self-efficacy. The subjects of this study were preservice teachers who were enrolled in a four-week (eight sessions) TRIZ invention course at a university in South Korea. A quasi-experimental method was used to incorporate TRIZ instructional strategies into an invention course that taught invention principles and hands-on activities. Results showed that the TRIZ instructional method significantly increased creativity beliefs, creativity, and invention teaching self-efficacy in preservice teachers. Interestingly, the TRIZ program had different effects on subdimensions of creativity. Results of the study suggest that TRIZ is an effective instructional method that can be used to increase teachers’ creativity, change their beliefs about creativity, and boost confidence in their invention teaching ability. Limitations and suggestions for future study are also discussed.

Teachers are gatekeepers of technology integration in the classroom. Pre-service teachers’ attitudes, confidence, and competence in exploring emerging technologies play a critical role in teachers’ adoption of technology in teaching. This study examined the effects of a gamified technology course on pre-service teachers’ confidence, intention, and motivation in integrating technology into teaching. A sample of pre-service teachers (N = 84) at a Midwestern university in the United States in the academic year of 2021–22 was surveyed. The regression results revealed that the gamified course significantly and positively influenced pre-service teachers’ confidence in using technology in education, intention to adopt gamification, and motivation to explore more emerging technologies for teaching, after controlling for gender. In contrast, gender did not affect pre-service teachers’ confidence, intention, and motivation in integrating technology into instruction after controlling for the gamified course effects. Suggestions on gamifying course design while leveraging quest-based learning and active learning principles to enhance student positive attitudes and motivation to explore technology integration are discussed.

Collaborative programming can develop computational thinking and knowledge of computational programming. However, the researchers pointed out that because students often fail to mobilize metacognition to regulate and control their cognitive activities in a cooperation, this results in poor learning effects. Especially low-achieving students need more metacognitive support. Therefore, this study proposed a metacognition-based collaborative programming approach (M-CPA) to improve students' performance in collaborative programming. To evaluate the effectiveness of the method for students with different levels of learning achievement, a 7-week experiment was conducted. A total of 222 middle school students were divided into the experimental group with the M-CPA learning and the control group with the conventional collaborative programming approach (C-CPA). The results showed that learning methods and learning achievement had interactive effects on computational thinking tendency, critical thinking tendency, and metacognition tendency. M-CPA could significantly improve students' computational thinking tendency, critical thinking tendency, and metacognition tendency. Moreover, the proposed approach is more effective for low-achieving students. The results also showed that M-CPA could improve the students' achievement in program analysis questions.

ABN (Abierto Basado en Números—Open Calculation Based on Numbers) is a method for teaching basic arithmetic operations in primary education that has become popular in recent years and that is based on the decomposition of numbers through manipulative materials that encourage mental calculation. Currently there is limited number of tools that can be used to support the ABN method and so this article presents the design and development of two tools that facilitate learning with this method, a physical device, ABENEARIO-P, and a virtual device (web application), ABENEARIO-V, that complements the physical device. In addition, a study of the use of these tools was carried out with 80 learners (ages 7 and 9) and 9 teachers with a focus on ABENEARIO-V. The results of this study showed a positive evaluation of the tool by both learners and teachers, an adequate time to complete the mathematical operations assigned to learners and an improvement in performance as the tool was used. As a conclusion, it is important to provide adequate tools that can support teachers and learners in the practice with the ABN method as in the case of ABENEARIO-P and ABENEARIO-V. Limitations refer mainly to the context of the study, which was conducted at a time of severe social distance restrictions during the COVID-19 pandemic on touching physical devices or being able to gather a larger number of learners in the classroom.

How instructional sequences guide learning processes are often regarded as a neutral act. However, does designing instruction carry a politics? This investigation explores how instruction is made as a pedagogical object. The purpose is to explore the epistemological principles and conceptual framework that produce instruction’s formalized pedagogical processes, each of which carries uncontested cultural and political aspects. Through textual analysis, the article considers theoretically and historically the problem of how instruction’s design entangles people, power, and technology to operate as social technology, making up human kinds when instruction is designed as rule-bound programming—as an algorithm. Such algorithms engineer cultural action to engineer more harmonious human relations, embodying a greater political project that closes a technocultural lag, ameliorating human deficiencies while producing social exclusion and inequality.

Cartoon images have been widely applied in children’s educational media. The study examined the effect of cartoon images in touchscreen media on young children’s recognition of time. With a 2 (clock type: cartoon clock, non-cartoon clock) × 2 (media type: touchscreen, video) between-subjects design, ninety-two children aged 4–6 were randomly assigned to one of four experimental conditions. Each group was exposed for 10 min to the media designed to teach children how to tell the time. We examined children’s learning to tell time by pre- and post-test clock tests. Results showed that: (1) In the condition of the cartoon clock, children in the touchscreen groups got significantly higher total clock learning scores than the video groups; (2) In the condition of touchscreen, children in the cartoon groups got significantly higher total clock learning scores than non-cartoon groups. Findings suggest that touchscreen interaction is more beneficial for children to learn to tell time than watching videos, and when using educational apps for touchscreen learning, cartoon images have a positive effect on children’s learning to tell time. However, cartoon images have no effect on children’s learning to tell time through videos.

The system of music education is directly attributed to arrangements that improve theoretical and working knowledge. Purpose of the article: the features of interactive methods that improve music literacy skills among students majoring in preschool education at teacher training universities, based on the Kodály method. Achievement of the set goal was possible as a result of involvement of 100 students and 55 preschoolers. Using the method of observation, the authors developed the following principles to improve the musical literacy of students: setting the voice with Erol Singer’s Studio; vocal performance of songs using active movements; learning from national vocal art, as well as academic foreign compositions; application of the soliloquy principle using the Sing Sharp app. In this study, using the calculation of the coefficient of effectiveness, the level of knowledge of students after the training was established. It was found that voice production without the involvement of a musical instrument and vocal performance of songs using active movements were developed to a greater extent (at a high level), because interactive technology was involved, promoting the assimilation of knowledge (Erol Singer’s Studio). Calculation of the knowledge efficiency of preschool children who were trained according to the developed principles showed that the greatest number of preschool children received a high level of knowledge, which is associated with their interest in learning. The paper’s practical implications are attributed to the possibility of applying the developed education principles for musical literacy improvement based on interactive teaching methods and the Kodály method. Further studies might measure the effectiveness of the developed teaching principles for a broader age group of students, which will help to track the positive (negative) effects of the curriculum on musical literacy skills.

The purpose of this study was to look into how Information and Communication Technology (ICT) is used in teaching English language from the point-of-view of English language teachers in Palestine. A quantitative approach was employed to collect data from 780 language school teachers from 260 schools who participated in a course project utilizing ICT in English as a Foreign Language teaching (TEFL). These participants responded to a questionnaire survey about the effects of the Covid-19 epidemic on language education and how they dealt with these. We statistically analysed the responses through four domains: the use of ICT in students’ lives; the use of ICT in education generally; the use of ICT to support learning and teaching in EFL; and teachers’ perceived skills for using ICT in education. Results indicated that English language teachers in Palestinian public schools believed that ICT has clear potential to support the learning of English, but that there remain barriers to its implementation. Teachers feel equipped to use ICT but would like to see a greater emphasis on training in order to maximise their teaching.

We know little to what extent peer feedback strategies can be applied on a large scale in higher education for complex tasks. This study aimed to design, implement, and evaluate an online-supported peer feedback module for large-scale use to enhance higher education students' argumentative essay writing performance. To do this, 330 students from five different courses at bachelor and master levels followed the online supported peer feedback module. In this module, students were asked to write an argumentative essay about a controversial issue, provide peer feedback for two peers, and revise their original essays based on the received feedback. Three types of data including original essay (pre-test) data, peer feedback data, and revised essay (post-test) data collected. Students also filled out the learning satisfaction questionnaire at the end of the module. The findings showed that the suggested online-supported peer feedback module was effective in improving stu-dents' argumentative essay quality in all courses at the bachelor and master levels. The findings also showed there is a difference in the level of students' satisfaction with the module among the courses and between the education levels. The findings of this study provide insights into and add value to the scalability of online peer feedback tools for argumentative essay writing in different contexts. Based on the findings, recommendations for future studies and educational practice are provided.

Flipped classroom (FC) has recently attracted researchers’ interest in teacher education thanks to its potential for promoting pre-service teachers’ (PTs) professional development. However, some of major issues are the lack of interactivity, disengagement, and amotivation of PTs for pre-class activities due to poor online instruction design. This explanatory sequential mixed study explores the effects of the microlearning-supported FC on PTs’ learning performance for professional development, motivation, and engagement. A total of 128 PTs participated in this study from a university in Turkey. In the quantitative phase, a quasi-experimental pretest-posttest design was conducted and the treatment lasted for 14 weeks. The PTs were divided into two experimental groups and one control groups using random sampling technique. In first experimental group (m-FC, n = 43), the participants learned with microlearning-supported (by using a-bit sized learning chunks outside the classroom) FC model. In the second experimental group (t-FC, n = 39), the participants learned with traditional FC model. A control group (non-FC, n = 46) was not taught using FC model and teacher-centered approach was adopted in this group. The findings indicated that FC model (in both experimental groups) increased learning performance, intrinsic motivation, emotional, and behavioral engagement compared to a group that was not used to FC. Moreover, m-FC group had better intrinsic motivation and engagement than both t-FC and non-FC groups. Semi-structured interviews showed that two major themes emerged regarding benefits and challenges of microlearning-supported FC. Most of PTs had positive perceptions that it enhances the willingness to participate in pre-class activities. The implications for teacher education, recommendations and directions for further studies were also discussed.

With a strong demand for online education and project management in deeper scope and larger scale to better fit COVID-19 pandemic situation, exploring new knowledge of online education to make it more effective became vital with the new challenges of STEM education. To resolve the above problem, this paper focuses on various aspects of online STEM education project management where the Enhanced Noyce Explorers, Scholars, Teachers (E-NEST) three-tiered structure was implemented during the COVID-19 period. Two City University of New York (CUNY) institutions, New York City College of Technology (City Tech) and Borough of Manhattan Community College (BMCC) used the three-tiered structure referred to as Explorer, Scholar and Teacher which incorporated advancements in teaching internships, professional development workshops and mentorships remotely. Built upon the theories of engagement, capacity and continuity (ECC) and team-based learning (TBL), this remote learning model and infrastructure had a positive impact on STEM education and project management. The technological tools utilized included Zoom, Google Meet, Microsoft teams, Blackboard Collaborate Ultra, Skype and SurveyMonkey. The results from qualitative and quantitative data including project evaluation, online surveys and focus group interviews demonstrate that the modified remote learning and management tools were effective. This indicated that the E-NEST model greatly supported student success and faculty in online learning and project management meetings. The E-NEST STEM education project was compared to two other project management models along with the previous NEST curriculum. Faculty emphasized practicing project management proactively and utilized best practices of classroom and time management consistent with Project Management Body of Knowledge (PMBOK) and Project Cycle Management (PCM) guidelines. The comparisons attest that the E-NEST project developed excellent and innovative online platforms for student learning with project management and ECC and TBL applications. Hereafter, this research can be used to constructively develop more online STEM education learning models and platforms and integrate new practice and technology globally. These ideas can contribute to future research that could be applied internationally to STEM education projects in K-12 and higher education institutions.

This study examines university faculty members’ successful behaviours and the factors influencing these behaviours, when dealing with the issues posed by emergency remote teaching during the COVID-19 pandemic. Data was gathered through interviews with 12 carefully chosen instructors who competently prepared and implemented their first online classes despite various challenges encountered during the crisis. Interview transcripts were analysed by applying the theoretical concepts of the positive deviance approach to identify exemplary behaviours in the face of crisis. The results revealed that the participants performed three unique but effective behaviours, called ‘positive deviance behaviours’, in their online teaching: philosophy-driven decision making informed planning and ongoing performance monitoring. These behaviours were affected by individual factors (e.g., community engagement and emotion management during different phases of emergency remote teaching) and organisational factors (e.g., networks/hardware and training/support). By examining the positive deviance behaviours of instructors who delivered effective classes, this study offers online teaching and faculty development strategies in both crisis and non-crisis situations.

Much research has been done on the benefits of video games in a physical education context (Camunas-Vega & Alcaide-Risoto, 2020; Fang et al., 2020). However, little attention has so far been paid to the effectiveness of commercial video games combined with actual basketball practice in helping students improve their reasoning skills (Chuang et al., 2021; Rogers et al., 2020). The study presents a quasi-experimental pre-post design with a control group in order to evaluate the impact of a specific training program in reasoning with the video game NBA 2K16. A convenience sample of 215 high school students participated in the study. Three reasoning subscales of the Evalua-9 psycho-pedagogical test (inductive α = 0.88; deductive α = 0.85; spatial α = 0.89) were used for data collection. Our findings show a significant moderate effect in the students who participated in the training program. An additional outcome was that sex differences in spatial and deductive reasoning in the pre-test disappeared in the post-test. We discuss the educational implications of the use of the video game as the main learning tool to enhance the reasoning process of Secondary Education students in Physical Education.

Article in Open Access (https://doi.org/10.1007/s10639-023-11612-z) New technologies have led to digital educational tools to improve learning. Game-Based Learning makes it possible to test whether there is a positive impact on official grades. We have collected the scores of the Kahoot! games, the marks of the continuous assessment, the final exam, and the final mark of the subject, to create an ad-hoc database. Finally, we have analyzed a database consisting of 392 marks of higher students from the first semester of the 2018/2019 academic year. We have calculated a correlation matrix, tested a hypothesis for differences in mean paired samples, and proposed three regression models to obtain that there is a positive influence of the games on the official marks. Therefore, Kahoot! is a didactic tool that improves students’ learning and is reflected in their official marks.

Wikidata is a free, multilingual, open knowledge-base that stores structured, linked data. It has grown rapidly and as of December 2022 contains over 100 million items and millions of statements, making it the largest semantic knowledge-base in existence. Changing the interaction between people and knowledge, Wikidata offers various learning opportunities, leading to new applications in sciences, technology and cultures. These learning opportunities stem in part from the ability to query this data and ask questions that were difficult to answer in the past. They also stem from the ability to visualize query results, for example on a timeline or a map, which, in turn, helps users make sense of the data and draw additional insights from it. Research on the semantic web as learning platform and on Wikidata in the context of education is almost non-existent, and we are just beginning to understand how to utilize it for educational purposes. This research investigates the Semantic Web as a learning platform, focusing on Wikidata as a prime example. To that end, a methodology of multiple case studies was adopted, demonstrating Wikidata uses by early adopters. Seven semi-structured, in-depth interviews were conducted, out of which 10 distinct projects were extracted. A thematic analysis approach was deployed, revealing eight main uses, as well as benefits and challenges to engaging with the platform. The results shed light on Wikidata’s potential as a lifelong learning process, enabling opportunities for improved Data Literacy and a worldwide social impact.

One of the most fundamental problems many students face in school is bullying. This form of harassment, known as cyberbullying, has emerged as the use of the internet and other digital media has increased in recent years. The purpose of this study is to determine the extent of secondary school students’ cyberbullying and cyber victimization experiences, to see if there is a correlation between cyberbullying and cyber victimization, and to explore how students’ cyberbullying or cyber victim status influences their cyber victim or cyberbullying behavior. Unlike experimental studies, which use manipulation and random assignment of participants and conditions, the study employed a causal-comparative research design, in which the researcher investigates the causes and consequences of differences between groups. The sample group of the study consists of 286 secondary school students in the fifth, sixth, and seventh grades who were recruited using the typical case sampling method, which is one of the purposive sampling methods. The data were collected via the scales of cyberbullying and cyber victimization. According to the findings, cyberbullying is significantly and positively influenced by cyber victimization. Instead of looking at cyberbullying in isolation, it was suggested that a more effective approach to solving the problem would be to integrate cyberbullying and cyber victimization holistically.

Considering the importance of group member familiarity in collaborative learning in classroom learning environments, this study examined the impact of group member familiarity on CSCL (computer-supported collaborative learning) in a net-worked setting. Also, the differences between CSCL in the online environments and FtF (face-to-face) collaborative learning were also compared. An analysis using structural equation modeling revealed that group member familiarity increased teamwork satisfaction, which in turn increased student engagement and perceived knowledge construction. A multi-group analysis revealed that while FtF collabora-tive learning exhibits higher levels of group member familiarity, teamwork satisfaction , student engagement, and perceived knowledge construction, the mediating effect of teamwork satisfaction was more pronounced in online settings. The study findings provided insights for teachers to improve collaborative learning experiences and adapt different teaching strategies.

The mental health of students learning online is a critical task for many countries around the globe. The research purpose was to analyse the factors affecting the quality of mental health of young individuals who learnt under conditions of not total lockdowns but adaptive quarantine restrictions. The research involved 186 volunteers from Zhengzhou University of Technology, 94 were first-year students, and 92 were fourth-year students. The experimental group involved first-year students, and the control group involved fourth-year students. An average age of the participants in the experimental group was 18.3 years, and in the control group, the average age was 22.4 years. The scholars conducted the research after four months of distance learning under the adaptive quarantine. The students could be involved in their usual entertainment activities and interpersonal communication outside the home. The Behavioural Health Measure, better known as BHM-20, was the core psychometric tool. The research finds that distance learning is less effective for first-year students than for fourth-year students because the former cannot effectively adapt and communicate in a new social environment, and develop trusting interpersonal relationships with fellow students and teachers. The research results coincide with other research on this issue and demonstrate a low degree of mental resilience during and after the pandemic. Previous research is not suitable for the analysis of the mental health of students under adaptive quarantine, including the freshmen, considered the most vulnerable group. The article will be useful for professionals interested in distance education in higher educational institutions, workers of socio-psychological services at universities or individuals involved in adapting curriculum materials for distance learning.

This study employed the design-based research (DBR) methodology to explore how to design instructional prompts integrated into a computer-based cognitive tool, GeoGebra, for gifted mathematics education. This study was divided into two iterative research phases lasting for 3 semesters, in which differentiating the instructional prompts for gifted students was explored. During two iterations, a combination of quantitative and qualitative data collection and analysis procedures were used to examine the effect of the designed prompts on gifted students’ learning achievements and explore their feedback on the learning activities based on the research conducted on 60 participants who were tenth-grade students. The findings led to a set of design propositions that contribute to the literature on both instructional prompts integrated into computer-based cognitive tools and gifted mathematics education. The propositions emphasize (a) prompts’ types, the algebraic-based prompts (ABPs) and software-based prompts (SBPs), (b) prompts’ order, emphasizing on presenting ABPs before SBPs, (c) prompts’ sequencing, adjusting the number of prompts’ sequences to gifted students’ characteristics, and (d) prompts’ combination, merging ABPs and SBPs to gain higher order learning outcomes. The prospective studies for the next phases of the DBR study are also discussed.

Using Virtual Reality (VR) in educational contexts is becoming increasingly common. The ability of VR to provide authentic learning experiences is making it a particularly promising platform for language learning, but the research on its acceptance among language teachers is scarce. This paper reports the results obtained from a large-scale (N = 2,176) survey on language teachers’ beliefs toward the use of VR for education. The survey explored the relationships between language teachers’ beliefs about using VR in a classroom and their teaching experiences, such as previous use of VR for teaching, their stages of VR technology integration, and their preferred teaching approaches. Furthermore, the survey yielded answers on the relationship between the availability of information technology (IT) personnel in language teachers’ schools. We found that practical knowledge and past experiences of incorporating VR in teaching were crucial determinants of teachers’ positive beliefs, showing that teachers were motivated to adopt VR technology in their classrooms if they had previously used it. Language teachers’ favorable beliefs were also positively correlated with the availability of IT personnel in their schools.

Sense of success and self-efficacy regarding technology integration in teaching are among the most important factors that influence teachers’ well-being and professional development, and may have a substantial impact on student learning. In this quantitative study (N = 735 K-12 teachers in Israel), we explored the factors contributing to sense of success in emergency remote teaching and self-efficacy for integrating technology in teaching following the experience of teaching during COVID-19 days. We use decision-tree models to look at nuanced relations. Overall, our findings highlight the crucial—albeit not surprising—role of experience in teaching with technology as an important factor that promotes sense of success and self-efficacy. Going beyond this factor, we emphasize that emotional difficulties in times of emergency may serve as an important risk factor, and that taking a leading role in school may serve as an important protective factor. We also found an advantage to STEM and Language teachers, compared with Social Sciences and Humanities teachers. Following our findings, we conclude with a set of recommendations that could enhance school-based teaching and learning at large.

This study aims to employ the supervised machine learning algorithms to examine factors that negatively impacted academic performance among college students on probation (underperforming students). We used the Knowledge Discovery in Databases (KDD) methodology on a sample of N = 6514 college students spanning 11 years (from 2009 to 2019) provided by a major public university in Oman. We used the Information Gain (InfoGain) algorithm to select the most effective features and ensemble methods to compare the accuracy with more robust algorithms, including Logit Boost, Vote, and Bagging. The algorithms were evaluated based on the performance evaluation metrics such as accuracy, precision, recall, F-measure, and ROC curve, and then validated using 10-folds cross-validation. The study revealed that the main identified factors affecting student academic achievement include study duration in the university and previous performance in secondary school. Based on the experimental results, these features were consistently ranked as the top factors that negatively impacted academic performance. The study also indicated that gender, estimated graduation year, cohort, and academic specialization significantly contributed to whether a student was under probation. Domain experts and other students were involved in verifying some of the results. The theoretical and practical implications of this study are discussed.

Since the covid pandemic, universities propose online education to ensure learning continuity. However, the insufficient preparation led to a major drop in the learner’s performance and his/her dissatisfaction with the learning experience. This may be due to several reasons, including the insensitivity of the virtual learning environment to the learner’s preferences. We propose to address the issue of student’s dissatisfaction and lack of interaction, by integrating learning style theory into the analysis of the learner’s online behavior. Our work differentiates itself from the rest of researches that employed learning style theory by its two step process. First, we classify the learning activities into learning categories based on learning style theory. Second, we define behavioral features that quantify the learner’s behavior across the learning categories. The analysis of the learner’s online behavior based on the behavioral features revealed new aspects of the learner’s preferences. We consider these findings to be best useful for developing learning style-sensitive adaptive learning environments. Nevertheless, the behavioral features could be beneficial in different contexts. In fact, when applied to course outcome prediction, the behavioral features enhanced the results by 10%. The latter indicates that behavioral features reflected the correlation between behavior and academic performance.

Social media use is widely accepted in higher education, connecting students’ learning with daily life. Considering the potential of social media to revolutionize the whole spectrum of teaching and learning, this study examines social media usage of business school students of different majors and their perception of social media as learning aids through a quantitative online survey guided by the 5E instructional model, with 423 valid responses from students majoring in accounting, finance, and economics. Results indicated that respondents perceived social media as influential in helping them access study-related information. It facilitated comprehensive learning, information access, information sharing, and student communication with instructors. Significant differences in perceptions of using social media as aids for business learning were found among students of different demographics, including gender, education level, and residence, but not quite for different majors. While various studies have examined the use of social media in education, scant studies focus on business school students under the lens of the 5E instructional model, especially Asians.

This article discusses the effect of using a commercial off-the-shelf immersive virtual reality game on engineering students’ reaction time, hand-eye coordination, and spatial skills. Fifteen (15) college engineering students in Northern Taiwan were conveniently recruited in a single group. Participants were tasked to play the game for 30 min during the intervention in one day. After the intervention, they were interviewed to explore more about their experiences. The approach showed significant improvement in hand-eye coordination with a large effect size. However, reaction time and spatial skills showed some mean differences, but they were not significant. The findings suggest that the adversary effect of cybersickness can be categorized as none to slight. Qualitative interviews were also conducted to gain better insights and explain the quantitative results. Most participants felt that the activities were fun and engaging. Therefore, it is suggested that the benefits of immersive virtual reality exceed their adverse effects.

Higher Education Institutions (HEIs) are involved in an evolution to a new model of university called digital university. This model implies not only adopting new technologies but also developing an organizational strategic transformation which includes information, processes, human aspects, and more. Because an organization’s digital maturity correlates with the scope of its digital transformation efforts, this study aims to identify digital transformation initiatives (DTI) taken by HEIs, defining the new processes and technologies used to implement them. The main motivation is to have a real and clear vision of how universities are transforming themselves, discovering the most relevant DTI that they have applied and if they are doing it through an integrated plan aligned with a digital strategy, as recommended by experts. We conducted a Multivocal Literature Review, as methodology research, to include both academic and grey literature in the analysis. Main results show that the DTI implemented are primarily focused on providing a quality and competitive education (24% of 184 DTI from 39 different universities analyzed). Emerging technologies most frequently used are advanced analytics (23%), cloud (20%) and artificial intelligence (16% of total DTI). We conclude that HEIs are in the first steps to digital maturity as only 1 in 4 have a digital strategy and 56% have launched isolated DTI that are not integrated in a plan and do not have a high strategic return value to the organization.

This study attempts to: (a) investigate whether positive and negative emotions mediate the pathways linking self-efficacy for learning programming with effort and persistence in undergraduates’ learning Scratch programming combining with a programmable hardware platform (i.e., Arduino), and (b) assess the effect of academic major (i.e., information technology-related majors vs non-information technology-related majors) on self-efficacy for learning programming and emotions. With the use of responses collected from a sample of 156 undergraduate students, the research model is empirically validated using partial least squares structural equation modeling (PLS-SEM). The findings reveal that undergraduates’ effort and persistence while learning programming were significantly predicted by positive emotions, but not by negative emotions. Self-efficacy for learning programming significantly and positively influenced positive emotions and negatively influenced negative emotions. Finally, variations in predicting positive emotions were found between different academic majors: students in information technology-related majors experienced less negative emotional experiences than those in non-information technology-related majors.

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