ETR&D

The purpose of the present study was to analyze the impact of technology on student foreign language learning, as it has been widely used to enhance language instruction over the past few decades. This multivariate meta–meta-analysis study aimed to examine the effects of technology on various aspects of language learning, including listening, speaking, reading, writing and vocabulary, and explore how factors like educational level and technology type influenced these impacts. The researchers conducted a meta-analysis of 10 studies published prior to May 2023, using both qualitative and quantitative methods. They analyzed the descriptive and methodological characteristics of each study, and found a statistically significant overall effect size (g = .068, p < .001 with a 95% confidence interval of .595–.860) indicating that technology positively impacted language learning outcomes compared to traditional learning methods. The researchers identified educational level and technology type as important factors contributing to the variability in effect size. Specifically, both higher education and K-12 settings, as well as VR tools and computing resources, had positive impacts on students’ foreign language learning. Overall, the results suggest that using technology is an effective way to improve foreign language learning for students, and provide valuable recommendations for future research and practical applications in this area.

Computational thinking is accepted today as a collection of cognitive and social skills required for functioning in the 21st century. The paper presents a conceptual view at computational thinking that encompass concepts, problem-solving skills, application skills, and social skills. To impart those perceptions and skills the paper proposes the Four Pedagogies for Developing Computational Thinking (4P4CT) framework, which relies on active learning, project-based learning, product-based learning, and context-based learning, and advocates implementing computational thinking across all the education system in all subject matters at all ages by all teachers. The framework is presented and its implementation in an academic course for preservice K-12 teachers, taught so far in 16 classes attended by 409 preservice K-12 teachers, is described in detail. To support the effective development of the expected competences among preservice teachers, two types of empirical qualitative evidence, related to student outcomes, are presented: (a) simulations of computational processes, and (b) reflections that indicate a change in preservice teachers' perceptions and the application of computational thinking in their future teaching work.

Computer-supported collaborative concept mapping (CSCCM), as one of the computer-mediated instruction and learning strategies, has been used to foster collaborative knowledge construction (CKC). Previous research has characterized groups based on final knowledge artifacts, products, or performances, rather than the temporal, process-oriented characteristics generated during the collaborative learning process. To fill this gap, this research clustered groups into distinct clusters based on the collaborative discourse data by using agglomerative hierarchical clustering approach, and examined the process characteristics of different clusters and associated performances. Four clusters were identified and labeled. Cluster 1, the high-performing cluster, was characterized as the actively-engaged, idea-centered, consensus-achieved, and socioemotional-engaged cluster. Cluster 2, the low-performing cluster, was characterized as the inactively-engaged, information-shared, goal-oriented, and reflection-revolved cluster. Cluster 3, the medium-performing cluster, was characterized as the inactively-engaged, problems-unsolved, and reflection-revolved cluster. Cluster 4, the medium-performing cluster, was characterized as the actively-engaged, idea-centered, and goal-oriented cluster. Based on the results, this research proposed instructional strategies and assessment implications for improving CSCCM research and practice.

Peer feedback is regarded as playing a vital role in fostering preservice teachers’ noticing and reasoning skills during technology integration. However, novices in particular (e.g., pre-service teachers) tend to provide rather superficial feedback, which does not necessarily contribute to professional development. Against this background, we developed an online video-annotation tool, LiveFeedback + , which allows for providing peer feedback on the quality of technology integration during microteachings in a fine-grained manner. Applying a design-based research approach (2 design cycles, N = 42 pre-service teachers, quasi-experimental interrupted time-series design), we investigated whether the addition of prompts (Cycle 1) and strategy instruction combined with prompts (Cycle 2) contributed to the quality of peer feedback. Contrary to our predictions, piecewise regressions demonstrated that pre-service teachers provided more feedback comments with superficial praise and fewer feedback comments with substantial problem identification and solutions when prompts were available. However, when pre-service teachers were explicitly instructed in strategy use, the reasoning during peer feedback could be enhanced to some extent, as pre-service teachers provided less praise and more problem diagnosis in feedback comments when strategy instruction was available. These findings suggest that the addition of strategy instruction that explicitly models adequate feedback strategies based on prompts can help overcome mediation deficits during peer feedback in technology-based settings.

With continued growth in online learning, motivation remains a key factor in persistence and achievement. Online mathematics students struggle with self-regulation and self-efficacy. As reported by Ryan and Deci (Self-determination theory: basic psychological needs in motivation, development, and wellness, Guilford Press, 2017, https://doi.org/10.3233/EFI-2004-22201), in their well-established self-determination theory, contended that satisfying the psychological needs of autonomy (involving self-regulation), competence (involving self-efficacy), and relatedness (involving a sense of belonging) creates a suitable environment for integrated extrinsic and intrinsic motivation to thrive. The purpose of this action research was to implement a self-determination theory-based online unit for mathematics students to improve their motivation levels. A convergent mixed methods action research design was employed to identify changes in the levels of autonomy, competence, and relatedness of the participants in an Algebra 2 course (n = 50) at a fully online school in the northeastern United States. Results from the motivation questionnaire and student interviews indicated a significant increase in competence and relatedness after completing the intervention. While no significant increase in autonomy was evident in the quantitative results, the qualitative findings showed some support for improved autonomy. Recommendations for online mathematics course design to support increased motivation are provided.

A chatbot is artificial intelligence software that converses with a user in natural language. It can be instrumental in mitigating teaching workloads by coaching or answering student inquiries. To understand student-chatbot interactions, this study is engineered to optimize student learning experience and instructional design. In this study, we developed a chatbot that supplemented disciplinary writing instructions to enhance peer reviewer’s feedback on draft essays. With 23 participants from a lower-division post-secondary education course, we delved into characteristics of student-chatbot interactions. Our analysis revealed students were often overconfident about their learning and comprehension. Drawing on these findings, we propose a new methodology to identify where improvements can be made in conversation patterns in educational chatbots. These guidelines include analyzing interaction pattern logs to progressively redesign chatbot scripts that improve discussions and optimize learning. We describe new methodology providing valuable insights for designing more effective instructional chatbots by enhancing and engaging student learning experiences through improved peer feedback.

Inquiry-based instruction has played an important role in science education, and been recognized as a critical approach to improve students’ scientific learning effectiveness. However, current research revealed that it is a challenge for teacher education programs to improve pre-service science teachers’ inquiry-based instructional activity design competency. Due to the dynamic and complicated process of the instructional design competency improvement, there is a strong need for new methods that could trace this process. Considering the Knowledge Integration (KI) theory has been demonstrated to be able to help science teachers design their inquiry-based instructional activities in a large amount of existing research, in this study, a KI-based collaborative learning environment was designed to support 19 pre-service science teachers’ inquiry-based instructional activity design. Epistemic network analysis (ENA) was applied to trace the development process of their inquiry-based instructional activity design e behaviour patterns. Data analysis results revealed that the pre-service science teachers demonstrated gradually more active in “guiding students to design exploratory activities” and “guiding students to communicate and cooperate” in their instructional designs during the process of using the KI-based collaborative learning environment. Through identifying and comparing the design patterns of the high-performing and low-performing groups, the results showed that the low-performing groups demonstrated more active on “posing inquiry questions” and “guiding students to formulate scientific explanation,” while the high performing groups demonstrated more active in “guiding students to design exploratory activities” and “guiding students to communicate and cooperate.” Furthermore, the semi-structured interview results demonstrated that the KI-based collaborative learning environment not only provided the pre-service science teachers a convenient way on online collaboration, but also helped them form more normative and integrated understandings on inquiry-based instruction. However, this study demonstrated that quite a few pre-service science teachers still had misconceptions on inquiry-based instruction. Suggestions are provided for improving pre-service science teachers’ inquiry-based instructional design competency in a technology-enhanced learning environment.

Two questions regarding text signals’ influence on second language (L2) science expository text comprehension were examined. First, the contextual relationship between verbal headings and non-verbal underlining signals (i.e., related or unrelated) was manipulated to investigate how these verbal and nonverbal text signals influence L2 text comprehension. Second, the physical distance between a heading and the underlined terms (i.e., close or distant) was manipulated to investigate how the physical proximity to the heading influences L2 text comprehension. University mixed proficiency Korean English language learners (n = 160) were randomly assigned to one of four conditions by proficiency level in a 2 (related or unrelated) × 2 (close or distant) design; one coherent text and three incoherent texts. Then all participants read assigned multiple-topic expository text, created a visual map of the text they read, and then completed a comprehension posttest (all in English). For the low proficient L2 readers, a heading served primarily as a general visual cue, leading the readers to respond only to underlined information regardless of the relatedness of heading and distance. For the high proficient L2 readers, a heading acted as a content-specific cue leading the readers to respond more to underlined information that related to the heading content and heading closeness. These results have direct instructional text design implications for organizing L2 expository texts for L2 readers.

K-12 educators who engage their students in designing using digital technologies face the challenge of teaching the act of designing in classroom contexts, yet books and articles on the topic of design processes and methods tend to focus on the instruction of design strategies for adult learners rather than children. One framework, the Informed Design Teaching and Learning Matrix (Crismond and Adams, Journal of Engineering Education 101:738–797, 2012) does address dimensions of design practices and instructional approaches specifically within K-16 educational contexts, but it has yet to be revised based on empirical evidence. Using multiple case studies, we examined this framework against teacher perceptions of how design should be taught and the observed instructional practices of those secondary educators. We argue that refinement to the IDTL Matrix is warranted and suggest expanding the framework to include design strategies that address collaborative learning, peer communication, and the integration of digital and non-digital tools and materials. Such revisions to the IDTL Matrix would contribute to providing the best possible support to teachers who seek to develop their students’ design strategies in classroom contexts.

In formal educational settings, such as online university lectures, instructional videos often consist of PowerPoint slides accompanied by a video or audio explanation from the instructor. It has been assumed that the social cues provided by the instructor’s video may facilitate affective processes and affect learning outcomes. Research on instructor presence in instructional videos has focused primarily on laboratory and online studies that are not embedded in the courses in which learners are enrolled. Therefore, we present three field studies examining instructor presence in instructional videos embedded in higher education courses to strengthen external validity (exam-relevant topic, > 30 min long, personally known instructor). The results of these studies show positive effects of a visible instructor compared to no visible instructor on some affective measures: social presence in Study 1 (n = 18, d = .85) and well-being in Study 3 (n = 38, d = 1.01), but not on others (well-being in Studies 1 & 2 (n = 53); motivation in Studies 1–3, social presence in Studies 2 & 3). They also show no effects on extraneous processing or learning outcomes (Studies 1–3). Thus, no general effect of instructor presence can be shown for instructional videos embedded in university courses in higher education, but there are also no detrimental effects. This leads to implications for future research, teaching, and design practice.

Computational thinking is acknowledged as an essential competency for everyone to learn. However, teachers find it challenging to implement the existing learning approaches in K-12 settings because the existing approaches often focus on teaching computing concepts and skills (i.e., programming skills) rather than on helping students develop their computational thinking competency—a competency that can be used across disciplinary boundaries in accordance with curriculum requirements. To address this need, the current study investigated how game-based learning influenced middle school students’ learning processes, particularly on the development of computational thinking competency, self-efficacy toward computational thinking, and engagement during gameplay. Additionally, the study examined how these outcomes were moderated by individual differences. We observed evidence that the gaming experience influenced students’ computational thinking self-efficacy, but not computational thinking competency or game-based engagement. Compared to age (grade) and prior gaming experience, gender tended to play a more important role in moderating students’ computational thinking competency, self-efficacy toward computational thinking competency, and game-based engagement. Implications and possible directions for future research regarding using game-based learning to enhance computational thinking competency are discussed.

Although the metaverse is a trending topic in several fields, it is not a new concept within the field of education. In this study, we followed the PRISMA framework and identified 37 articles since 2008 that researched the metaverse in education. We critically reviewed these articles, aiming to examine the evolution of the field’s conceptual understanding of the metaverse in education, identify its applications and effects, as well as synthesize the technical solutions and adoption challenges for implementing metaverse systems in schools. We found that the early empirical implementation of metaverse concepts in education mainly emphasized the characteristics of 3D virtual environments and avatars using the Second Life and OpenSim platforms. These traditional applications were found to be effective in supporting various teaching methods and enhancing students’ learning experiences and outcomes. In recent studies, more advanced technologies that pursue the fusion of physical and virtual environments (e.g. AI techniques, VR/AR devices, cloud platforms, wearable devices) have been incorporated into metaverse systems. However, the extent to which physical and virtual environments were fused in metaverse applications in education needs to be further clarified. We suggest that the conceptual clarity of the metaverse in education will keep evolving along with the technology development, and teacher preparedness for this new technical revolution needs more attention.

A majority of research in Computational Thinking (CT) mainly focuses on teaching coding to school students. However, CT involves more than just coding and includes other skills like algorithmic thinking. The current study developed an Online Inquiry-based Learning Platform for Computational Thinking (CT-ONLINQ) that follows Inquiry-Based Learning (IBL) pedagogy to support CT activities. IBL-based CT steps include algorithm design, analysis, and comparison of algorithms. Also, the platform allows students to explore multiple solutions to a problem and provides multiple-try feedback with hints as support during problem-solving activities. The hint generation strategy uses a Knowledge Graph that captures knowledge about the problem's solution in a machine-processible form. A six-week quasi-experimental study was conducted to determine the effectiveness of multiple-try feedback with hints on students’ CT skills. The study included 79 high school students: 41 students as part of the experimental group (EG) were provided problem-specific hints, and 38 as part of the control group (CG) with CT-general hints. The results showed that the students in the EG group improved their CT skills significantly more than those in the CG group. In addition, the study also evaluates the effectiveness of intervention considering biases in gender and prior coding experience. Female students performed better than male students in both groups after the intervention. Furthermore, in EG group, observations showed that students without coding experience performed better than their counterparts with experience. The findings suggest that the IBL-based CT activity on CT-ONLINQ can be deployed to improve the CT skills of school students.

Recent years have seen an increase in the use of immersive virtual reality (IVR) technology in education and training. Studies examining the efficacy of IVR-based interventions have shown improved performance compared to traditional training programmes; however, little is known about whether such improvements can be detected at the level of individual cognitive abilities. The present study sought to examine the effect of IVR on memory using an incidental learning paradigm. Undergraduate volunteers viewed a three-minute 360° video clip under immersive and non-immersive conditions—respectively, using a Head Mounted Display (HMD) or a 2D flat screen monitor—followed by a surprise recall task. Although both devices supported active exploration of the scene in 360°, recall was significantly improved for learners in the immersive condition. These findings suggest that IVR has a facilitative effect on cognition, and that learners may naturally engage with IVR-delivered content without any special instruction or preparation.

This study aimed to examine the effect of four types of assessment on overall student success in an online college-level climate change course. Quizzes, midterms, lab assignments, and a capstone project as well as knowledge check questions were used to assess different aspects of student learning, consistent with Bloom’s taxonomy hierarchy. Quizzes and midterms assess basic knowledge, including remembering and understanding concepts, laboratory assignments require students to analyze and integrate concepts, and the capstone allows students to evaluate their understanding and create new content. Binary logistic regression, multiple regression analysis, continuous-by-continuous interaction modeling, and path analysis were used to investigate the moderating and mediating effects of these assessment types. We found both direct and indirect positive interactions as well as one negative interaction. Positive interactions were identified between quiz and lab assignment achievement and between capstone achievement and lab assignment achievement. The total score for correctly answered knowledge check questions positively affected quiz and lab assignment achievements. The interaction between capstone project achievement and total score for correctly answered knowledge check questions showed a negative interaction. Finally, the total score for correctly answered knowledge-check questions had an indirect positive effect on overall student success in the course. Results show that different types of assessment in an online course are complementary and amplify student learning.

Researchers have indicated the importance of engaging learners in self-regulated learning (SRL) states when situated in game-based learning contexts; however, it remains a challenge for both educational and educational technology researchers to effectively integrate both. To this end, this study investigated how SRL strategies are interwoven with game-based learning in higher education by searching the web of science database to systematically review the papers published between 2009 and 2020 in academic journals. The encoded dimensions ranged from the primary research purpose to research issues, including application domains, research methods, duration of the studies, SRL strategies, game types, and game genres. It was found that since 2015, the research purposes have become increasingly diverse, with skills acquisition in game-based learning being regarded as the most important goal, followed by knowledge acquisition and behavior change. Such games took goal orientation, peer learning, and regulating as the main SRL strategies, which exerted a positive effect on learning performance, self-efficacy/confidence, attitudes/effort, satisfaction/interest, and learning behavior. Meanwhile, these SRL strategies were well embedded into problem-solving, simulation, multi-type, and RPG game types against the setting of the real-life-related storyline as the main game genre. Since previous studies lacked the systematic application of all SRL strategies within a game-based learning environment, they could not uncover the dynamic and cyclic processes of SRL in game-based learning environments. Hence, this study proposed corresponding suggestions for future research issues as a reference for researchers, teachers, and decision-makers.

The effectiveness of digital game-based language learning (DGBLL) has been recognized by scholars. With the development of computer technology and multimedia learning environments, computer agents have been widely used in game systems to provide learning guidance or assistance. A computer agent is a virtual character created in a digital learning system to achieve instructional goals. However, in traditional teaching systems, computer agents are designed to perform a single role, such as a teacher or a student. Computer agents with a single interactive logic often lack the functionality required to understand students’ conditions and needs from various perspectives, and cannot adapt for better learning support. Therefore, this study proposed an adaptive role-switching strategy that allows computer agents to adjust their roles and functions according to students' needs in digital games to promote their learning achievement. An adaptive computer agent-based digital game was developed to investigate the impact of this model on English vocabulary learning achievement, motivation, self-efficacy, and English anxiety among EFL (English as Foreign Language) students. A quasi-experiment was designed and 56 middle school students in four classes were recruited. Two classes (n = 30) were arranged to be the experimental group which used an adaptive computer agent-based digital game (adaptive computer agent-based digital game, ACA-DG), while two classes (n = 26) were arranged to be the control group which used the conventional computer agent-based digital game (conventional computer agent-based digital game, CCA-DG). The results showed that students in the experimental group had significantly higher learning achievement and self-efficacy than those in the control group. On the other hand, students in the experimental group had significantly lower English anxiety than those in the control group. There was no significant difference between the two groups regarding learning motivation.

In the contemporary society, it is important to cultivate students’ visual literacy. However, there has been a lack of sufficient training for students to improve their visual literacy in the classroom. A problem-posing approach (Visual Thinking Strategy, VTS, a learning strategy with question sequences to facilitate critical inquiry) has been proposed to achieve this objective. However, problem-posing should be supported with scaffolds to help learning deeply. And concept mapping is such a scaffold to aid problem-posing in visual literacy cultivation. In this study, a quasi-experiment was conducted on two classes of undergraduate students in Shanghai to evaluate the effects of the proposed approach. An online learning system was developed based on the proposed approach; moreover, a quasi-experiment was conducted on two classes of undergraduate students to evaluate the effects of the proposed approach. The experimental results show that the concept mapping-based online problem-posing approach improved the depth of students’ visual analysis, which indicates sharpening of students’ visual literacy and their critical thinking tendency. The interview results further showed that the students perceived the approach as being effective from the perspectives of “increasing visual analysis capability,” “developing thinking capability,” and “improving self-reflection in learning.”