Research and Practice in Technology Enhanced Learning

A conceptual research framework for sustainable digital learning in higher education

Mostafa Hamadi — 2024-01-01

The integration of digital technologies in Higher Education (HE) has dramatically changed the way students learn, however it has also raised critical concerns about the sustainability aspects of digital learning. Although a considerable amount of literature has been published on digital learning and Sustainable Development (SD) in HE, further research is needed to establish a comprehensive research framework which synthesises and organises the knowledge in this area. This paper draws on a critical review of the literature to develop a conceptual research framework on sustainable digital learning in HE from an Information Systems’ lens. The proposed framework is the outcome of a thorough integrative review, followed by a thematic analysis of relevant sources which outlines common research themes in the literature and identifies major areas for future research. The proposed framework provides researchers and educators with valuable insights on the use of digital technologies to promote SD in HE and highlights the importance of sustainability awareness. It further defines focus areas and future research directions which can guide their research, thereby assisting in building a coherent body of knowledge in this research area.

Loneliness, academic self-efficacy, and student engagement in the online learning environment: the role of humor in learning

Muhammad Ramli — 2024-01-01

This study investigated the impact of loneliness on academic self-efficacy (ASE) and student engagement in the context of remote teaching during the COVID-19 pandemic. Moreover, as a boundary condition, we examined the role of intermediate ASE in the relationship between loneliness, student engagement, and perceived humor in learning. A total of 367 undergraduate students from six universities in Indonesia completed an online questionnaire. Data were analyzed using Macro Process version 4 to test the moderating mediation model hypothesis. As expected, the study results show that loneliness is negatively related to ASE and student engagement. ASE is proven to affect student engagement positively; concurrently, it plays an intermediate role in the link between loneliness and student engagement. Finally, humor had a significant moderating effect on learning in the tested model. This study contributes to the existing literature on loneliness and student engagement by uncovering the intermediate role of ASE. Drawing on the social cognitive theory (SCT) and instructional humor processing theory (IHTP), we explored how perceived humor in learning moderates the relationships between loneliness, ASE, and student engagement.

How personal, technical, social environments affecting generation Z to utilise video-based sharing platform in learning process during crisis?

Dedi I. Inan — 2024-01-01

In a crisis such as COVID-19 that struck the world in 2019, social and community activities are restricted, including in-person classes. On the one hand, these restrictions are aimed as a precautionary measure against the virus spread; on the other hand, this could lead to a lost generation without an educational process. Notwithstanding this, online learning through a video-sharing platform is envisaged as the best way to keep learning in this particular situation. However, students have their learning style preferences. While a video-based sharing platform is seen as the most representative way of facilitating self-directed learning, understanding the motivations driving the adoption is crucial. This paper investigates technical, social, and personal environments that motivate generation Z to utilise this tool for self-directed learning, employing Social Cognitive Theory (SCT) as the theoretical lens. A total of 251 survey responses from this cohort were collected and analysed with a structural equation modelling approach. The findings reveal that perceived usefulness and content quality, peer influence, and self-efficacy and outcome from three perspectives, respectively, determine the adoption intention substantially by 67.1%. These findings provide several important implications for video-sharing platform acceptance in terms of both research and practice. Limitations and future research directions are also discussed.

Digital information literacy, self-directed learning, and personal knowledge management in critical readers: Application of IDC Theory

Moloud Mohammadi — 2024-01-01

The usefulness of self-directed learning ability in education has been demonstrated in previous studies. However, there has been much less understanding of the importance of digital information literacy, as well as how to manage these abilities and knowledge, and their effects on learning processes, especially in the current situation of digital education dominance and the necessity of interest creation in students. In order to address such needs and to evaluate students, as well as determine the effectiveness of the Interest-Driven Creator (IDC) loops, this study was conducted. In this study, 164 English language students were asked to participate in the pre-test, treatment, and post-test processes, while the treatments for the IDC group were developed in the form of interest-creation-habit triple loops. The results represented that IDC hybrid instruction was more effective in strengthening digital information literacy and personal knowledge management; and the IDC hybrid group outperformed the non-IDC hybrid group in terms of self-directed learning skills. These findings also revealed that to develop self-directed learning in critical readers, in addition to digital skills and how to manage and apply acquired knowledge, learning instructions (i.e., interest-creation-habit loops) have been effective. The IDC-hybrid group also identified the features of participation, perception-interest and facility-opportunity as the most significant and tangible ones.

Meaningful ICT integration into deprived rural communities’ multigrade classrooms

Luis Arturo Ávila-Meléndez — 2024-01-01

An innovation project’s key features for meaningful information and communication technologies (ICT) integration into multigrade classrooms of non-internet access and deprived rural communities are explored. Although the project implementation achievement differed in each school, the article focuses on the concurrent conditions that enabled ICT integration in some cases. The research evidence stems from open structured interviews in six multigrade primary schools and two regional workshops, and one selected lesson’s focused ethnography. Considering a wide-ranging ICT integration impediment review, it stands out the value of the Project’s lesson planning model that, in turn, has features suited to traditional student autonomy rooted in Mexican rural schools. The conclusion is that the synergy occurred amongst a minimum of equipment and digital resources, a planning model highlighting academic subject links, learning activities based on multi-modal resources, and the tradition of student autonomy. Even though the Project’s digital technologies are not cutting-edge, their innovative adaptation to multigrade schools in deprived communities is a pressing necessity in many countries.

What we have learned from adult students’ online learning experiences to enhance online learning of other students’ groups?

Olga Rotar — 2024-01-01

Adults used to be the largest online student population before the COVID-19 pandemic. However, the number of online students multiplied during the pandemic, and now includes the complete conglomeration of all student groups. Due to their longer experience of online education, adult students continue to provide valuable insights on how to enhance online learning for other higher education students. This article reports the results of phenomenographic research on the qualitative differences in the ways of experiencing learning by fifteen adult students enrolled in two online postgraduate programmes. The analysis on in-depth, participant-led interviews demonstrated that online learning is conceptualised in three ways: as an investment, as a process that brings structure, and as a process that enables and empowers an individual. The results of this study are of particular importance for those who are concerned with introducing online learning to the higher education curricula. The paper argues that the stigma of online education being the second choice, maintained in the educational research literature, should be replaced by a holistic approach to education as a process that organically incorporates the online educational elements into higher education. Focusing on how adult students experience online learning provides a broader and deeper understanding of adopted effective practices and the variety of online learning opportunities and outcomes for other students’ groups. Insights based on the results of this study are summarised.

How can an educational chatbot’s feedback influence human attention?

Francesca Sylvester — 2024-01-01

Educational chatbots have been shown to be useful assistants in computer-supported learning settings. However, how does feedback of an educational chatbot impact on the learner’s attention? Thus, this paper proposes a study to measure changes in human attention when learning by using an educational chatbot Liza that is intended to improve human reasoning ability. In total, 18 participants participated in the study and had a conversation with Liza. During the interaction with Liza, the attention of the study participants was measured using a mobile electroencephalogram (EEG) device. Three findings have been determined based on statistics methods. First, it was found that there was a significant attention effect occurring in 54% of the times, after the educational chatbot showed feedback and the attention measurement took place over the length of a task. Second, when differentiating the type of feedback, positive feedback had a significant effect in 71 of these 137 cases (51.82%) and negative feedback had a significant effect in 66 of the 137 cases (48.18%). Third, statistical results showed that there was no significant difference in attention at the significant level of 0.05 during the 10 seconds before, and 10 seconds after positive feedback is received. Similar is the case for negative feedback.

An exploratory study of pre-service teachers’ perceptions of technological pedagogical content knowledge of digital games

Yu-Chun Kuo — 2024-01-01

This study investigated pre-service teachers’ perceptions of technological pedagogical content knowledge of digital games (TPACK-G), the correlation of TPACK-G constructs, and the relation of TPACK-G to personal factors and levels of motivation and self-efficacy. Participants were 96 pre-service teachers from a university in the northeastern United States. Data were collected using online surveys. Quantitative approaches were performed to analyze the data. Results indicated that game content knowledge (GCK) and game pedagogical knowledge (GPK) significantly predicted pre-service teachers’ game pedagogical content knowledge (GPCK), with GPK being the strongest predictor. Pre-service teachers with high levels of motivation or self-efficacy for digital game integration had significantly better TPACK-G than those with low levels. Personal factors, including gender and prior experiences with digital games, were found to be influential to pre-service teachers’ TPACK-G. This study adds to the understanding of the application of the TPACK model in the context of digital game use for pre-service teachers.

Shelter GO: multiplayer location-based game to promote knowing shelters for emergency evacuation

Hiroyuki Mitsuhara — 2024-01-01

In the event of a disaster, we evacuate to a shelter. However, if we do not know where to go for refuge, we consume time or end ourselves at an unknown shelter. Furthermore, we cannot decide on a suitable shelter if we do not know its capacities and features. To promote knowing shelters in advance is essential for successful emergency evacuation. A promoting approach is the use of a location-based game. Thus, a prototype of a multiplayer location-based game known as “Shelter GO” was developed to promote players to become acquainted with shelters by adopting a game element similar to Pokémon GO. The game feature allows players to not only earn points by visiting and observing shelters and collecting digital creatures at disaster-related spots but also exchange their collected digital creatures with encountered players. The digital creature exchange entails knowledge exchange. A preliminary comparative experiment demonstrated that Shelter GO can promote knowing shelters and that knowledge exchange may not be frequently done but promote knowing shelters.

Partnership models in online learning design and the barriers for successful collaboration

Olga Rotar — 2024-01-01

The design of quality online courses is a team task, as this process requires multiple areas of expertise that are not typically possessed by a single individual. Yet, existing models of stakeholder partnerships in online learning design, and their nature, has yet to be explored in depth. This study was designed to address this gap. Using the PRISMA guidance, twenty-one articles that documented the experience of teamwork in designing online courses or programmes were analysed. For each study, a reported partnership model, stakeholders involved in the teamwork, and barriers to their communication were considered. Six partnership models in online learning design were identified: mentoring and guidance; equal collaboration; technical or formal support; multisectoral collaboration; focus on relationship building; and an iterative or flexible approach. Key barriers to establishing successful partnerships include poor knowledge of the design process, lack of financial incentives, no adequate regulation of the design process, insufficient project planning and management, time constraints and required time commitments, increased workload, and psychological barriers.

Learning behavioral patterns of students with varying performance in a high school mathematics course using an e-book system

Xuewang Geng — 2024-01-01

Traditional textbooks are progressively being replaced by e-book systems, which are also being utilized more commonly in K–12 education. The study investigated learning behavioral patterns in a seven-week high school mathematics course using an e-book system. In this study, learning data from the BookRoll system was analyzed with lag sequential analysis to examine learning behavioral patterns, learning strategies, and the differences between students with different performances. The results of the learning behavior patterns of all students confirmed the usage of rehearsal and elaboration strategies. However, it demonstrated the lack of using metacognitive strategies in the e-book learning process. Additionally, the results also revealed different learning patterns among students with different learning performances. Students with decreased performance tended to use shallow cognitive processing strategies, while students with increased performance used deeper learning strategies, such as integrating information from the previous and next pages to highlight learning contents. Regarding the strategy usage of students with unchanged performance, students in the unchanged low and middle performance groups tended to utilize the re-reading strategy, while students in the unchanged high performance group utilized the elaboration strategy. Notably, students with increased performance employed fewer learning behavioral patterns than decreased performance students. The behavioral patterns of students with increased performance were more efficient and effective.

Language learning apps for visually impaired users: a systematic review

Heydy Robles — 2024-01-01

The purpose of this literature review is to identify, categorize, and critically appraise research papers related to mobile apps for visually impaired people in language learning. This study intended to identify the language skills, the affordances, and the limitations encountered while designing and implementing the apps. Hence, a systematic review in the Scopus database and the virtual libraries of IEEE, SAGE, ERIC, and Science Direct, adhering to the PRISMA methodology, produced 274 research papers, and after the application of the different phases, a detailed analysis was performed using 17 articles. The results revealed that Information Communication Technologies, assistive technologies, and electronic accessibility features contributed to the usability guidelines and the current evolution toward modern language learning mobile applications for visually impaired users. The revised work also revealed how writing, reading, and spelling became more demanding for this particular special need, and that grammar-based and traditional activities are replaced by other communicative approaches. The emphasis was on speaking and listening skills due to these being less demanding in terms of technical requirements. The findings of this review provide insights for instructional designers to construct inclusive language learning apps which consider the three essential dimensions needed to achieve it: technological, pedagogical and psychological, in addition to appropriate affordances necessary for both sighted and visually impaired users.

A competency-based specialization course for smart city professionals

Theodor Panagiotakopoulos — 2024-01-01

Intelligent technologies permeate all aspects of contemporary society and urban life. It is essential to educate the workforce of smart cities in order to effectively meet emerging technological demands. In this paper, we present an e-course that focuses on discrete competencies associated with different smart city roles. Initially, we present the conceptual learning framework for the development of the competency-based learning course and we define the objectives of the research. The paper continues with a discussion of the model’s application steps and an examination of the course’s skills, competencies, and roles. The acquired knowledge was measured using pre- and post-course tests, and questionnaires were used to investigate the relevance and quality of the learning material and the learning acquisition of the participants. Evaluation results showed that the course was relevant to the concept of smart cities, useful for their work duties, while participation in the course resulted in increased overall competency in all three smart city job profiles.

A systematic review of online teaching competencies in higher education context: a multilevel model for professional development

Hossein Chaharbashloo — 2024-01-01

The explosive growth of online learning in higher education (HE) institutions has resulted in an unprecedented need to develop comprehensive professional development programs in order to support HE instructors in online settings. The purpose of this systematic review is to identify and categorize online teaching competencies in HE and to propose a conceptual model for creating professional learning opportunities within such settings. Following a rigorous systematic search in two electronic databases (Web of Science and Scopus) between the years 1993 to 2023, 77 eligible articles were chosen and analyzed through content analysis. A total of 106 competencies were identified under seven overarching dimensions. Inspired by the emerged dimensions of the identified competencies, a three-level model for establishing professional development programs for HE institutions is presented and the implications for HE instructors and institutions are discussed.

Automated grading software tool with feedback process to support learning of hardware description languages

Andrés Francisco Corso Pinzón — 2024-01-01

Hardware Description Languages (HDL) have gained popularity in the field of digital electronics design, driven by the increasing complexity of modern electronic circuits. Consequently, supporting students in their learning of these languages is crucial. This work aims to address this need by developing an automated assessment software tool with feedback process to support the learning of HDL and making an educational intervention to support the learning process of students. The tool’s features were selected based on similar developments, and a prototype was designed and implemented. Additionally, an educational intervention was conducted over a five-week period in a Digital Electronics course at the National University of Colombia. Through analyzing students’ interactions with the tool and their perceptions of its usage, the study examined their learning experiences. Among the features highlighted by students as most beneficial for their HDL learning process were the online availability of the tool, the feedback system that helped them identify and correct errors in their code, the provision of immediate feedback, the online editor with syntax highlighting, and the graphical user interface. This work makes two significant contributions to the field of HDL teaching in engineering. Firstly, a publicly accessible HDL grading tool has been developed, offering students immediate formative and summative feedback through an automated grader. Secondly, empirical evidence has been provided regarding the benefits of using such a tool in enhancing students’ learning process.

Unsupervised techniques for generating a standard sample self-explanation answer with knowledge components in a math quiz

Ryosuke Nakamoto — 2024-01-01

Self-explanation is a widely recognized and effective pedagogical method. Previous research has indicated that self-explanation can be used to evaluate students’ comprehension and identify their areas of difficulty on mathematical quizzes. However, most analytical techniques necessitate pre-labeled materials, which limits the potential for large-scale study. Conversely, utilizing collected self-explanations without supervision is challenging because there is little research on this topic. Therefore, this study aims to investigate the feasibility of automatically generating a standardized self-explanation sample answer from unsupervised collected self-explanations. The proposed model involves preprocessing and three machine learning steps: vectorization, clustering, and extraction. Experiments involving 1,434 self-explanation answers from 25 quizzes indicate that 72% of the quizzes generate sample answers containing all the necessary knowledge components. The similarity between human-generated and machine-generated sentences was significant with moderate positive correlation, r(23) = .48, p < .05.The best-performing generative model also achieved a high BERTScore of 0.715. Regarding the readability of the generated sample answers, the average score of the human-generated sentences was superior to that of the machine-generated ones. These results suggest that the proposed model can generate sample answers that contain critical knowledge components and can be further improved with BERTScore. This study is expected to have numerous applications, including identifying students’ areas of difficulty, scoring self-explanations, presenting students with reference materials for learning, and automatically generating scaffolding templates to train self-explanation skills.

Staff and student experiences of hybrid teaching in a pandemic-impacted context

Aisling Tierney — 2024-01-01

This paper presents the findings of qualitative and quantitative research of staff and students’ experience of hybrid teaching at the University of Bristol during the 2020/2021 academic year. Hybrid teaching was added as an additional mode of teaching and learning as a response to circumstances caused by the Covid-19 pandemic. The research analyses data collected from student focus groups, and staff and student questionnaires. The benefits and drawbacks of hybrid teaching are presented in relation to trends in the higher education sector. The paper demonstrates the value of multi-method approaches to data collection to test the validity of institutional use of hybrid teaching with reference to the literature. The research contributes to a gap in empirical evidence and suggests practical and theoretical parameters for considering the use of hybrid.

The Digital Pedagogy Competence Scale (DiPeCoS): development and validation

Shraddha Rawat — 2024-01-01

Digital pedagogy is the intentional integration of technology into teaching and learning to build rich learning experiences. Given this potential and the pace of the digitization of education, it is important to define, assess and develop teachers’ digital pedagogical competence. Although there are several self-report measures that assess digital pedagogy competence, these do not include scenario-based tools. Scenario-based assessments allow the evaluation of knowledge and skills in real-world applications. We present here the Digital Pedagogy Competence Scale (DiPeCoS), a short, scenario-based tool that assesses a teacher’s digital pedagogy competence through choices made in real-world teaching and learning scenarios. An initial pool of ten items was reduced to create an eight-item scale using item response analysis, which was subsequently validated on 1,315 teachers in India. The DiPeCoS demonstrates unidimensionality, and its constituent items show acceptable levels of discrimination, difficulty and guessing parameters and reliability. Our results indicate that such a tool is valuable in assessing teachers’ digital pedagogy competence, and we hope it finds value in the field of digital pedagogical training and evaluation.

EXAIT: Educational eXplainable Artificial Intelligent Tools for personalized learning

Hiroaki Ogata — 2024-01-01

As artificial intelligence systems increasingly make high-stakes recommendations and decisions automatically in many facets of our lives, the use of explainable artificial intelligence to inform stakeholders about the reasons behind such systems has been gaining much attention in a wide range of fields, including education. Also, in the field of education there has been a long history of research into self-explanation, where students explain the process of their answers. This has been recognized as a beneficial intervention to promote metacognitive skills, however, there is also unexplored potential to gain insight into the problems that learners experience due to inadequate prerequisite knowledge and skills that are required, or in the process of their application to the task at hand. While this aspect of self-explanation has been of interest to teachers, there is little research into the use of such information to inform educational AI systems. In this paper, we propose a system in which both students and the AI system explain to each other their reasons behind decisions that were made, such as: self-explanation of student cognition during the answering process, and explanation of recommendations based on internal mechanizes and other abstract representations of model algorithms.

Beyond recommendation acceptance: explanation’s learning effects in a math recommender system

Yiling Dai — 2024-01-01

Recommender systems can provide personalized advice on learning for individual students. Providing explanations of those recommendations are expected to increase the transparency and persuasiveness of the system, thus improve students’ adoption of the recommendation. Little research has explored the explanations’ practical effects on learning performance except for the acceptance of recommended learning activities. The recommendation explanations can improve the learning performance if the explanations are designed to contribute to relevant learning skills. This study conducted a comparative experiment (N = 276) in high school classrooms, aiming to investigate whether the use of an explainable math recommender system improves students’ learning performance. We found that the presence of the explanations had positive effects on students’ learning improvement and perceptions of the systems, but not the number of solved quizzes during the learning task. These results imply the possibility that the recommendation explanations may affect students’ meta-cognitive skills and their perceptions, which further contribute to students’ learning improvement. When separating the students based on their prior math abilities, we found a significant correlation between the number of viewed recommendations and the final learning improvement for the students with lower math abilities. This indicates that the students with lower math abilities may benefit from reading their learning progress indicated in the explanations. For students with higher math abilities, their learning improvement was more related to the behavior to select and solve recommended quizzes, which indicates a necessity of more sophisticated and interactive recommender system.

Evaluating the kit-build concept mapping process using sub-map scoring

Ridwan Rismanto — 2024-01-01

Concept mapping allows learners to visually represent their knowledge by connecting nodes (concepts) and links (relations between concepts). The kit-build (KB) concept map framework enhances this process by enabling learners to recompose a concept map from provided nodes and links, leading to improved learning outcomes. Additionally, KB employs an automatic assessment method called “Full Map Scoring (FMS)”, which evaluates the learner’s understanding based on the recomposed concept map. However, FMS only evaluates the final product of the recomposition activity, neglecting the process itself. This is a potential limitation because different processes leading to the same result could reflect different levels of understanding among learners. Therefore, it is crucial to incorporate process analysis into learner assessment. To address this issue, our research proposes a new assessment procedure termed “Sub-Map Scoring (SMS)”. A concept map is generally composed of several sub-maps with each sub-map representing a set of meanings. We hypothesize that if a learner comprehends the meaning of a sub-map, the learner will recompose the sub-map as a continuous activity. Therefore, SMS evaluates the recomposition process of each sub-map from the viewpoint of continuity, and the overall SMS score is derived from these evaluations. To verify the effectiveness of SMS, we compared SMS and FMS scores using data from a practical use of the KB framework. A multiple linear regression analysis confirmed that the SMS score was a more precise predictor of learning gain than the FMS score.

Online collaborative writing in an online EFL writing class

Burcu Ocak Kılınç — 2024-01-01

Most learners of English as a Foreign Language (EFL) consider writing a challenging task, and they experience difficulties such as organizing thoughts, selecting relevant words to represent their views, and producing rhetorical patterns specific to the target culture. Research into L2 writing suggests that collaboration in the classroom can assist students to set goals, generate ideas, write and edit, and reflect on the task. The effects of collaboration in online classes, however, remain unknown. This quasi-experimental study aims to examine the effect of online collaborative writing (OCW) in an online EFL writing class on students’ writing performance in terms of syntactic complexity, lexical complexity, and fluency. A four-week OCW intervention was carried out with 26 university students enrolled in an online English writing course at A2 level in the Common European Framework of Reference for Languages (CEFR). Data were collected using writing tasks administered as pre- and post-tests. Fluency, syntactic and lexical complexity were measured and analyzed across tasks. The results showed that OCW in an online EFL writing course improved the lexical complexity and fluency of the writings of students with an A2 level of English proficiency but had no effect on their syntactic complexity. Based on the findings, it is possible to conclude that OCW can be employed to promote students’ writing performance in online EFL classes.

AI to the rescue: Exploring the potential of ChatGPT as a teacher ally for workload relief and burnout prevention

Reem Hashem — 2024-01-01

This research investigates the effectiveness of AI generative ChatGPT as a teacher assistant to reduce workload and prevent burnout in secondary schools. Lesson planning and content development were significant contributors to teacher burnout. In response, ChatGPT was tested with tailored queries for English, science, and math subjects, utilising an explanatory research approach to assess ChatGPT’s capabilities in personalised planning and content development, given that there is limited available information around this topic. The study highlights ChatGPT’s benefits in personalised planning through task-specific prompts and AI-human collaboration. Aligned with UAE’s AI integration objectives, the study emphasises balanced use and educational reform potential. Integrating AI tools optimises teacher planning, enhances instructional support, and refines resource allocation, contributing to AI’s academic potential while stressing burnout mitigation’s importance for educational advancement.

“I felt like I was on campus” creating a situated learning environment through Instagram

Wangda Zhu — 2024-01-01

The transition to online learning due to COVID-19 brought opportunities for applying Situated Learning Theory through mobile social media to enhance individual cognitive growth and community sense of belonging in online learning environments. In this study, we invited students from an Environmental Psychology course to participate in a semester-long project, during which they were required to post Instagram photos of their surrounding environments every week. We intend to understand the mechanism of integrating social media (Instagram) into a hybrid class amid the global pandemic, and how the project affects students’ learning experience. Through in-depth interviews with 22 study participants, we found that integrating Instagram into the course helped students effectively connect with both real contexts and their peers. The project enhanced participants’ situation awareness and a sense of belonging through posting, interacting with peers, and browsing profiles and posts. We then proposed a framework of creating a situated learning environment through social media using conjecture mapping to inform design implications and future studies in social and mobile learning communities.

The influence of gender on STEM career choice: A partial least squares analysis

Tiny Chiu Yuen Tey — 2024-01-01

Students’ participation in science, technology, engineering, and mathematics (STEM) is still one of the most critical worldwide educational challenges despite efforts to promote STEM. Debates about gender disparities in STEM careers also remain perpetual. Early documented literature suggested shifts in students’ STEM choices were due to students’ significant others, media exposure and attitude. Therefore, the first aim of this paper was to examine the direct and indirect relationships in a proposed model, and analyze the mediating roles of media exposure and students’ attitude in the relationship between subjective norms and STEM career choice intention. The second aim was to analyze the moderating role of students’ gender. Respondents of this study were 806 secondary school students in Malaysia. Based on the results from partial least squares structural equation modeling, (i) subjective norms had both direct and indirect influence on students’ career choice intention in STEM, (ii) media exposure and students’ attitude were significant mediators between subjective norms and career choice intention in STEM, and (iii) gender moderated the influence of subjective norms on media exposure. The findings drawn from this study provide insights into the design and development of STEM initiatives for parents, teachers, and peers by considering the importance of the media, students’ attitude, and gender. Recommendations for policy and practice enhancements were suggested for future research directions to support STEM interventions in Malaysia.

Classroom implementation of an auxiliary problem presentation system for mechanics adapted to learners’ errors

Nonoka Aikawa — 2024-01-01

Error-based Simulation (EBS) is a learning support framework that visualizes learners’ errors and encourages trial and error. However, when a learner is stuck, EBS has difficulty in helping them overcome the impasse. Additionally, giving a correct answer to a learner who is stuck may interfere with the trial-and-error activity that EBS is oriented toward. Therefore, it is necessary to encourage learners during trial-and-error activities without giving them correct answers. In this study, we confirm the effectiveness of our system, which is based on conventional mechanics EBS and provides adaptive auxiliary problems based on learners’ errors. Furthermore, we analyze force-based self-overcoming to evaluate our system. Self-overcoming means that the learner can eliminate errors by using the system without the intervention of the teacher. If self-overcoming occurs, the learner can continue trial-and-error with the auxiliary problems, even if they are stuck. To verify the learning effectiveness of such a system, we conducted a classroom implementation with 86 third-year junior high-school learners and analyzed the results. The system logs from the exercises revealed that self-overcoming was taking place, and that it was reflected in the test results.

Correlation among game addiction, achievement emotion, and learning motivation: A study of Indonesian youth in the context of e-learning system

Rona Nisa Sofia Amriza — 2024-01-01

This study investigated the correlation between game addiction, achievement emotions, and motivation in the e-learning context. This research collected data through an online questionnaire that briefly explained the study’s aim, demographic questions, the Game Addiction Scale (GAS), the e-Learning Achievement Emotion Questionnaire (eLAEQ), and the e-Learning Motivation Scale (eLMS). 607 high school, undergraduate, and graduate students participated in this study — Data analysis involved the utilization of structural equation modeling. The study findings reveal that game addiction substantially impacts positive and negative emotions and intrinsic and extrinsic learning motivations. Moreover, positive emotions significantly affect intrinsic and extrinsic learning motivations. Conversely, negative emotions have a substantial impact on intrinsic learning motivation but not on extrinsic learning motivation.

A human-in-the-loop system for labeling knowledge components in Japanese mathematics exercises

Brendan Flanagan — 2024-01-01

Many modern learning systems rely on a data representation of the knowledge that is to be learned to estimate a learner’s mastery state and recommend appropriate learning tasks to further improve their acquisition of knowledge and skills. In particular, the rapid development of intelligent tutoring systems (ITS) and standardized curricula has increased the need for information on knowledge structures and their links to learning materials and tasks. However, manually labeling educational data has traditionally been a time-consuming, labor-intensive task, and thus has limited its use by time-constrained teachers and practitioners. In previous research, a range of machine-learning methods have been proposed to address this problem, with only a few of them focusing on Japanese educational datasets from secondary schools. In this paper, to support the labeling of Japanese mathematics exercises by teachers and other domain experts, we apply natural language processing techniques including word-embedding and key-phrase-based exercise-to-exercise similarity methods. We evaluated the proposed method by both the performance of the models when compared to several state-of-the-art methods, and also its effectiveness in supporting humans in the task of labeling educational materials. Through this two-phase evaluation, we found that the proposed method outperformed other methods, and when implemented in a human-in-the-loop system it achieved significantly more accuracy and consumed less time for the task of labeling mathematics exercises.

An investigation of students and teachers’ new media literacy: the contributing characteristics with the moderator role of gender

Mehmet Vergili — 2024-01-05

This study aims to investigate students and teachers’ new media literacy in addition to the contributing factors with a relatively large sample size. In this sense, the current study is considered unique as it provides findings from both student and teacher participants, and investigates the contributing factors to their new media literacy with the moderation of gender. The new media literacy framework was adopted as the theoretical base, and students and teachers’ new media literacy was investigated in terms of consuming and prosuming dimensions. The data were collected from 1195 students studying in primary, middle, and high schools (including rural and urban areas) and 581 teachers. The findings revealed that teachers’ literacy is higher than students’ at all educational levels for all dimensions of the new media literacy framework. It was also found that students’ educational level and ICT teachers’ subject field positively contribute to their literacies in all dimensions. While teachers’ age negatively contributes only to their prosuming skills, it has no influence on their consuming skills. Finally, no significant moderating effect of gender was observed on these relationships while it is found as a predictor of both students and teachers’ prosuming skills, and also teachers’ functional consuming skills. For these skills in both groups, male participants demonstrated higher literacy than females. Rather than generational differences, the findings underline the role of formal and informal experience in the development of digital literacies, particularly in critical dimensions, and were further discussed based on the current literature.

A pedagogical design for self-regulated learning in academic writing using text-based generative artificial intelligence tools: 6-P pedagogy of plan, prompt, preview, produce, peer-review, portfolio-tracking

Siu-Cheung Kong — 2024-01-15

The emergence and popularity of generative artificial intelligence (AI) tools, particularly text-based ones known as large language models, pose both opportunities and challenges to education. The ability of these tools to generate human-like texts based on minimal instructions causes concerns among educators about students’ use of these tools for academic writing, which may constitute a breach of academic integrity. We propose a pedagogical design that models on self-regulated learning and the authoring cycle and develops students’ critical thinking and self-regulation when composing academic writing using text-based generative AI tools. It contains six iterative and interactive phases. Students first plan the content and structure of the writing, then generate prompts for text-based generative AI tools. Next, students preview and verify the tools’ output, followed by the fourth phase of producing the writing using the corrected output. Fifthly, peer review by fellow students may be required to polish and proofread the writing. Lastly, through portfolio-tracking, students reflect on the writing process, and formulate strategies for future usage of text-based generative AI tools for writing. This pedagogical design helps students and teachers embrace text-based generative AI while addressing the perils these tools present, and guides the development of education interventions and instruments.

Gender differences in achievement, behavior, and STEM interest among learners using Minecraft

Maricel A. Esclamado — 2024-01-26

In this paper, we analyze how male and female learners differ in their in-game behaviors, knowledge assessment outcomes, and STEM interest using the What-If Hypothetical Implementations using Minecraft (WHIMC). We also investigate how male and female learners’ self-reported levels of frustration and boredom relate to these outcomes. We examine in-game data, out-of-game assessment data, self-reported frustration and boredom, and results of the STEM interest questionnaire (SIQ) from 175 Grade 8 learners from a school in the Philippines. We found that male learners tend to explore more than female learners. Both genders learn more through more exploration, making more observations, and completing tasks, but only female learners benefit from having more idle time. Male learners had a higher increase in STEM interest compared to female learners, while there is no significant difference in assessment scores between the genders. This study also found that boredom and frustration have a negative impact on academic outcomes, behavior, and STEM interest, especially among female learners. Bored female learners tend to do less well on post-game assessments, explore less, and make fewer observations. Frustrated female learners tend to not complete the task. Female learners who expressed frustration or boredom tend to have a decreased interest in SIQ in the Interest category after playing WHIMC.

Development and validation of a blended learning perception scale for higher vocational students

Wuxue Jiang — 2024-01-31

Blended learning, a pedagogical approach that seamlessly integrates online and offline teaching methods, has evolved into a pivotal component of higher education. In order to assess students’ perspectives on their experiences with blended learning in higher vocational schools, we developed a comprehensive tool known as the Blended Learning Perception Scale (BLPS). The scale’s reliability and validity have been rigorously substantiated through data obtained from 600 students enrolled in a vocational school in China. The creation of this scale primarily entailed the application of quantitative methodologies, including both exploratory and confirmatory factor analyses. The final scale encompasses 24 items, categorizing student perceptions into five distinct factors: content coherence, interaction effectiveness, platform functionality, learning motivation, and learning satisfaction. Collectively, these factors elucidate 68.346% of the total variance. Moreover, the Cronbach’s coefficients (α) for these factors range from 0.791 to 0.842, denoting a high degree of internal consistency and thereby establishing the scale’s reliability. Item-based analysis further substantiates the scale’s reliability and discriminability, while confirmatory factor analysis unequivocally confirms its structural validity. Each factor’s average variance extracted (AVE) ranges from 0.589 to 0.671, with a cumulative value of 2.766. Additionally, the Root Mean Square Error of Approximation (RSMEA) recorded at 0.053 underscores the scale’s satisfactory level of structural validity. In essence, this study presents a valid and dependable instrument for gauging students’ perceptions of blended learning, thoughtfully tailored to the specific attributes of higher vocational education and its students. Furthermore, it offers insights into areas that necessitate further enhancement within blended learning programs.

Is it useful, acceptable, or controllable? Hong Kong primary school teachers’ online assessment practices in changing time

Ying Zhan — 2024-02-15

Few studies have explored primary school teachers’ classroom-based online assessment practices and underlying reasons. To fill this research gap, this study interviewed 48 Hong Kong primary school teachers to understand their online assessment practices and influencing factors when they were obliged to use it in their daily instruction under the influence of the COVID-19 pandemic. The findings revealed that the participants tended to use online tests/exercises for formative purposes instead of summative purposes. In addition, they tried online alternative assessment tasks, such as video or audio recordings, peer assessment and projects, and gave online feedback to students but less frequently than online tests/exercises. The school examination culture and the participants’ perceived limited control over online test fairness may have restricted their summative use of online tests/exercises. Meanwhile, the participants’ perceived positive usage norms, along with their favourable attitudes towards and confidence in using online tests/exercises probably enhanced their formative use of them. In addition, the participants’ perceived neutral usage norms and limited external control of online alternative assessment tasks and feedback seemed to impede their use of them in classrooms.

Learning analytics for student homework activities during a long break: Evidence from K-12 education in Japan

Hiroyuki Kuromiya — 2024-03-20

Learning Analytics (LA) is an emergent field that aims to better understand students and provide intelligence to learners, teachers, and administrators using learning log data. Although the use of technology in class is increasing in the K-12 sector and tertiary education, cases of effective implementation of LA in secondary schools have rarely been reported. This study offers an example of LA implemented in a junior high Math class during long vacations in Japan. This paper comprises two studies: first, we analyzed 121 students’ answer logs and their exam performance after vacation by the K-means clustering method. We found that students’ progress patterns were categorized into four types of engagement—early, late, high, and low—and the early and high-engagement groups obtained significantly higher scores than the low-engagement group. In the second study, we implemented a real-time dashboard that visualizes students’ progress patterns and gives students insights about their progress during the vacation period. We found that the dashboard significantly increased students’ interactions with the assignment, and the questionnaire survey determined that the LA dashboard motivated students to learn during the long vacation period. Considering the previous studies of LA, we estimate that LA-based interventions enhance students’ self-regulation skills, which is crucial for learning during long vacation periods. Our study offers a novel approach to implementing LA in K-12 education.

Developing and validating an AI-supported teaching applications’ self-efficacy scale

Chun-Mei Chou — 2024-03-28

This study was to construct and verify a teacher Artificial Intelligence (AI) supported teaching applications self-efficacy (AIS-TASE) measurement to examine reliability and validity and to explore the relationship between teachers' AIS-TASE and behaviour. There were 1456 high school teachers from 45 schools. The analysis results indicated that the scale has reliability, validity, and model adaptation. The scale can be used as a tool for teachers to judge themselves in AI-supported teaching. The scale for AIS-TASE includes five constructs: self-affirmation, willingness to teach, adherence to hard work, negative consciousness, and positive belief. From the analysis research of background variables, it is found that when teachers use technology-instruction integration AI experience, their perception use AI-supported technology in school and have a positive attitude towards AI experience on "self-affirmation," "teaching intention," and "positive belief." The measurement can reflect teachers' effectiveness evaluation in AI-supported teaching, which has important implications for the theoretical research and practical application in emerging technology teaching. This research discusses the practical in AI-supported teaching.

Creating authentic and effective practice scenarios for digital simulation-based conversation training

Natasha Gousseva — 2024-04-02

In this article, we describe and illustrate a five-step process model for designing practice scenarios for digital simulation-based conversation training, in which learners practice challenging conversations with a virtual character. To maximize the likelihood of a successful learning experience, it is important that these practice scenarios are perceived as authentic by learners, and that they are based on relevant theory and validated expertise from experienced professionals. Our process model describes the steps that developers can take to (1) uncover implicit expertise concerning professional conversations, (2) build a validated conversation model including feasible response options and (3) optimize the play experience so that learners feel sufficiently immersed and engaged while using the simulation-based training. The design process, which is cyclical in nature, is illustrated by means of a case study in which we developed a training for cross-cultural job interviews. Furthermore, we provide practical templates and examples of questions that can be asked to experts and learners during preliminary testing of the scenario. By doing so, we aim to make the process of designing training scenarios more transparent and duplicable, and help developers to avoid pitfalls and tackle conceptual and practical challenges that arise during the design process.