ETR&D

The current systematic review study explores instructional designer practices to develop a comprehensive understanding of strategies employed by instructional designers and the expectations of the field. Using the PRISMA protocol, a total of 98 articles were included in the review consisting of 65 qualitative, 15 quantitative, and 18 mixed-methods studies. Instructional designer practices were analyzed through the lens of 10 different topical areas: (1) Attitudes and perceptions, (2) decision-making and design judgments, (3) design strategies, (4) professional development and professional identity, (5) design heuristics, (6) instructional designer and faculty relationships, (7) instructional design competencies, (8) problem-solving, (9) instructional design teams, (9) instructional design teams, (10) change management and organizational development. Evidence-based recommendations and suggestions for practices of current and future instructional designers were discussed.

Teaching Computer Science concepts, such as graph theory, is often challenging. This study proposes an approach for teaching graph theory using an unplugged game (GraphGame) developed through a participatory design process that includes usage observation, clarifying meaning, prototyping, and implementation. This process was carried out with a group of Brazilian middle school students and involved collecting observations, interviews, ideation activities, and iterative prototyping with quantitative and qualitative tests. The game offers an interactive way to explore graph algorithms, improving abstraction capacity, a skill related to Computational Thinking. The effectiveness of the game in facilitating the learning of fundamental graphs concepts among high school students was evaluated with an independent sample of students. The results pointed out the proposal as a promising alternative for teaching graph theory, a complex computing topic, in an engaging way. By enhancing playful learning, this work offers an alternative to make teaching Computer Science more enjoyable and effective.

The formation of the digital divide is influenced by both objective factors, such as insufficient digital resources, and subjective factors, such as technology acceptance. This study employs a mixed-methods approach, utilizing the KANO model to analyze learners' demand attributes and the UTAUT model to examine subjective factors influencing technology acceptance. Standardized tests and survey questionnaires are used to assess digital learning outcomes. By collecting and analyzing data from diverse learner groups, this study aims to explore strategies for bridging the digital divide when transforming traditional online education into intelligent education, particularly in technologically and infrastructurally underdeveloped regions, including developing countries. The findings indicate significant differences in demand priorities among learners, as well as notable variations in how different learner groups classify their learning needs. Based on the demand analysis, targeted functional development can be implemented to reduce development costs in developing countries while maintaining the accessibility of digital resources. Moreover, user preferences for digital learning vary across groups; AI-driven identification and personalized recommendations can facilitate a more inclusive and equitable digital learning environment. Additionally, lowering the barriers to technology use through AI, enhancing engagement, and improving perceived effectiveness can significantly strengthen learners' confidence and motivation in bridging the digital divide. Finally, governments, educational institutions, and corporations should establish stronger communication and collaboration mechanisms to jointly address the pervasive digital divide in the era of intelligent education, particularly in developing countries.

This study investigated the effectiveness of localized learning content (LLC) in enhancing computational thinking (CT) skills and learning motivation among 6th-grade elementary school students in Busan, South Korea. In contrast to conventional methodological approaches, our research focuses on the transformative power of culturally and contextually relevant educational content. The study involved eight classroom teachers and 153 students, half of whom were exposed to programming education based on LLC and the other half to a conventional curriculum approved by the Ministry of Education. Quantitative analysis revealed a statistically significant improvement in CT skills and learning motivation among students in the LLC group compared to those in the control group, with effect sizes indicating a moderate magnitude of improvement. Semi-structured interviews with teachers and students supported these findings, indicating higher engagement and perceived relevance of LLC-based courses. However, this study also uncovered challenges related to the time and resources required to develop localized content. Despite these limitations, this study supports the potential utility of LLC, aligning with the sociocultural theory and the information process theory. It also opens new avenues for future research into LLC’s long-term efficacy and logistical feasibility. Given the significant improvements in CT and student motivation, the findings underscore the potential of LLC as a transformative approach in software education.

Writing explanations is widely recognized as an effective strategy to promote meaningful learning outcomes. However, most research focused on writing explanations for fictitious peers, with limited investigation into the benefits of writing for actual peers, particularly considering the influence of peer relationship closeness. To address this gap, the present study examined how explanation type (writing explanations vs. viewing explanations) and peer relationship closeness (close peer vs. distant peer) affect student’s perceived learning experience, attention allocation, behavior patterns, metacognitive judgment, and learning performance (i.e., retention and transfer). Our findings indicate that close peer relationships enhance student motivation and mental effort without increasing perceived difficulty. Furthermore, our results highlight the benefits of writing explanations, especially for a close peer, in enhancing students’ metacognitive judgment, self-monitoring behavior, and learning performance. These results lead to a recommendation to form strategic pairs or small groups in generative learning activities.

The adoption of blended and hybrid Flipped Classroom (FC) models increased dramatically during COVID-19 and is still highly valued and recommended for enhancing the quality, flexibility, and effectiveness of teaching and learning post-pandemic. While meta-analyses indicate a small yet meaningful effect size of the FC approach, examined studies often lack theoretical groundings and/or explicit design frameworks. As a result, there is an ever-increasing need for instructional design guidance for effectively integrating and facilitating online and in-person learning in the FC context. The current paper outlines a framework intended to guide educators, designers, and researchers to maximize the synergy of online and in-person learning as they design and implement FC. Grounded in (Merrill, First principles of instruction: Identifying and designing effective, efficient and engaging instruction, Pfeiffer, 2013) First Principles of Instruction, (Zimmerman and Schunk, Zimmerman and Schunk (eds), Handbook of self-regulation of learning and performance, Routledge, 2011) Self-Regulated Learning process, (Jones, Motivating students by design: Practical strategies for professors, CreateSpace, 2018) MUSIC Model of Academic Motivation, and (Flavell, American Psychologist 34:906, 1979) Metacognition theory, we first present a conceptual framework with flipped learning cycle, self-regulated learning cycle, and metacognitive FC orientation. Informed by these theories and our FC design experience across disciplines, we convert the conceptual framework into a procedural framework by organizing the design aspects and components into a generic FC learning process. Finally, we propose theoretically and empirically grounded design strategies for individual components of the FC process, which can be further validated and refined through iterative educational design research.

Artificial Intelligence (AI) tools are becoming increasingly popular in education, providing teachers with new opportunities to enhance student learning experience and build upon existing teaching practices. This study employs a co-design approach to develop AI-integrated learning materials and explore their implementation in elementary classrooms. In collaboration with researchers, twenty-five in-service teachers co-designed engaging, age-appropriate lesson plans aligned with the national elementary curriculum and adaptable to diverse classroom needs. Qualitative analysis of teachers’ focus groups (n = 25) highlighted the co-design approach's role in empowering teachers, fostering a sense of ownership, encouraging knowledge-sharing, and promoting collaboration and enthusiasm. A pilot study conducted in four elementary classrooms with 62 students evaluated the AI-integrated lesson plans and materials through quantitative survey data (n = 62). Findings indicate that students found the AI-supported learning experience enjoyable, engaging, and meaningful, particularly in deepening their understanding of literacy concepts. This paper presents the co-designed materials and provides insights for practitioners and researchers on the future of AI-powered education, offering potential directions for further research.

In educational settings, gamified learning integrates a variety of game elements to improve the learning experience, but a thorough analysis comparing different combinations of these elements is sparse. This meta-analysis consolidated data from 182 effect sizes across 37 randomized or quasi-randomized trials to assess the impact of gamified learning on student outcomes. Statistical analyses were conducted with gamified learning as the independent variable, learning outcomes as the dependent variable, and learning domain, learning stage, and intervention duration as moderating variables. The study aimed to evaluate the overall effect of gamified learning and to determine the most effective combinations of game elements. The results revealed a medium positive effect of gamified learning on learning outcomes (d = 0.566), with the “Rules/Goals + Challenge + Mystery” combination yielding the highest impact. And significant moderation was observed regarding the learning domain and the duration of the intervention. These findings offer valuable guidance for the design and application of gamified learning strategies, highlighting the need to consider moderating factors in educational practice.

Generative Artificial Intelligence (GAI) has received widespread attention recently, influencing teacher education in various ways. However, there is little discussion on pre-service teachers’ behavioral intention towards GAI. Therefore, this study employs subjective norm, AI self-efficacy, facilitating conditions, and trust to expand the Technology Acceptance Model, understanding pre-service teachers’ adoption of GAI. The study involves 486 undergraduates from a university in Jiangsu Province, China. The Partial Least Squares Structural Equation Model is used to test the research model. Research model proved to be both reliable and valid, confirming nine out of ten hypotheses. The findings indicate that: (1) AI self-efficacy strongly predicts perceived ease of use; (2) The most direct and strongest impact on perceived usefulness is perceived ease of use, followed by facilitating conditions; (3) Perceived ease of use doesn’t directly affect attitude towards use, but perceived usefulness and trust significantly influence this attitude; (4) Attitude towards use greatly predicts behavioral intention, followed by perceived usefulness and subjective norm. This research helps in advancing policy development in educational institutions and the integration of GAI and teacher education.

Computational thinking (CT) skills have become increasingly important in modern education, as they equip students with critical problem-solving skills applicable across various domains. Given the growing emphasis on digital literacy, it is essential to investigate grade- and gender-level differences in CT skills among students to support targeted interventions and to ensure that all students have equal opportunities to succeed in the digital age. This study examined CT skill development among primary school students, taking both grade- and gender-level disparities into account. Using quantitative data from a diverse sample of 517 primary school students, we conducted a comprehensive analysis of their CT scores. The results revealed no significant gender differences in CT scores among primary school students. However, notable age-related disparities emerged, with CT scores rising as students progressed through higher grades. This finding underscores the importance of considering developmental factors in CT education and highlights the need for age-appropriate CT curricula. By investigating both grade- and gender-level differences, this study aims to support educators and policymakers in developing more inclusive and effective strategies for cultivating CT skills among young learners, thereby preparing them for the challenges of the digital age.

Many universities utilized a reactive, piecemeal approach to adapt and rapidly reopen schools at the onset of the COVID-19 pandemic. Although schools were able to resume classes online relatively quickly, there was limited time to explore best practices for an optimal online learning environment. The pandemic exposed significant issues in the technological infrastructure at universities that impacted revenue, enrollment, and the overall learning environment. The technological infrastructure encompasses online teaching/learning, virtual engagement, and billing practices for distance education. While billing for distance education is not commonly included as a part of a university’s digital framework, we contend that it is a pivotal issue that could impact operational efficiencies. Tuition/fee rates and enrollment numbers for online vs. face-to-face courses in 50 US schools are explored. A review of the literature, anecdotal evidence, paired t-tests, and descriptive statistics reveal similar trends; for most universities, if tuition/fee rates for students that have the same residency status are compared, there are significant differences in the cost for online and face-to-face courses. The impact of these billing disparities, within the context of a university’s digital infrastructure, is also explored. Ultimately, this research paper highlights challenges and strategies to improve faculty preparation, technology, internet access, assessments, exam proctoring/supervision, IT support, learning management systems, and billing in a virtual learning/teaching environment.

The potential of immersive virtual reality (IVR) to deliver engaging occupational safety training has been established by previous research; however, to date, there have not been any pedagogical models to guide its implementation. This study’s objective was to conceptualize a pedagogical model for IVR safety training by combining a multidisciplinary theoretical framework with safety trainers’ contextual and pedagogical expertise. The research questions were (1) what kind of pedagogical practices do trainers apply in safety training, and (2) how do the trainers’ pedagogical practices inform the sociocultural contextualization of the pedagogical model for IVR safety training? Eighteen safety trainers were interviewed across two work organizations. An inductive approach was used in the interview data analysis. Three main categories of pedagogical practices were identified: (1) matching pedagogy to training goals, (2) guiding social interaction in training situations, and (3) utilizing organizational resources for training development. The findings extended our understanding of the sociocultural training context and provided insight into the pedagogical practices used in safety training. Based on the findings, pre- and post-training activities were added to the pedagogical model, and the descriptions of trainers’ actions during the facilitated introduction and debriefing phases were modified to support the training’s relevance to the learners, trainers, and organizations. This study illustrates a pragmatic approach to developing safety training in the context of advanced learning technology in design-based research. The pedagogical model will be applicable by training and education providers in IVR safety training across industries and in practice-based learning.

The measurable effects of music in online learning remains a topic of extensive debate, largely due to inconsistent findings within existing literature. Many of these inconclusive results stem from research methodologies that focus on singular perspectives, often overlooking a balance between cognitive challenges and emotional benefits of background music. Consequently, educators and instructional designers frequently overlook the potential of music to enhance learning experiences and offer new resources to explore emotion regulation. This perspective article offers a comprehensive and balanced examination of leveraging music’s benefits in online education. In this article, we synthesize recent theories across music cognition, educational psychology, instructional technology, empirical studies, and documented applications of music within online instructional contexts. Based on this analysis, we present three evidence-based propositions: (1) a refined theoretical framework elucidating music’s influence on behavior and learning outcomes, (2) four strategies to harness music for enhancing learner motivation, engagement, and comprehension, (3) guidelines and reflections for effectively integrating music into instructional design. The manuscript concludes with suggestions for mobilizing the four propositions and leveraging generative AI to enhance the role of music in learning, and the further steps that researchers and practitioners can take to implement music in online learning.

This case study investigates how a designed learning environment cultivates a “sense of promisingness”—an ability to discern what may work in uncertain conditions, essential for creative expertise. The study focused on 32 in-service teachers enrolled in a Master’s program in Taiwan, who engaged in mutually-supportive development of their thesis proposals over 18 weeks using the Knowledge Forum (KF) online tool. To evaluate the development of a sense of promisingness, we analyzed online discussion content where participants expressed their understanding of “what may work, how, and why” for improving their thesis proposals. We particularly examined three types of discourse moves—sharing-, argument-, and integration-oriented—to identify conditions fostering this ability. Key findings revealed that (1) sharing-oriented discourse was necessary but not sufficient for promoting the sense of promisingness, and (2) increased effort in integration-oriented discourse moves correlated with a higher likelihood of developing this ability. The study demonstrates that the course activity, designed based on knowledge-building principles in KF, serves as an effective instructional intervention for cultivating a sense of promisingness among graduate students. This research addresses a gap in the literature regarding methods to develop such knowledge-creating sense and the role of different discourse moves in sustaining knowledge advancement in online learning environments. The paper concludes with design implications for similar educational contexts.

Psychomotor skill training has traditionally relied on the physical presence of both teacher and learner for effective demonstrations and feedback, posing challenges for remote and self-directed learning. Technological advancements have given rise to immersive learning environments (ILEs), offering novel solutions for interactive and multimodal training. Despite the widespread use of technologies, comprehensive insights into the potential and specific advantages of ILEs within the psychomotor domain remain understudied. This systematic literature review investigates current research on ILEs tailored for psychomotor skill development, focusing on four key dimensions: motor skill classification, technological integration, feedback mechanisms, and design characteristics of virtual environments. By conducting frequency and correlation analyses, the review identifies positive correlations that suggest potential synergies between various aspects of ILE-based psychomotor training and highlights research gaps through negative correlations. The findings offer a comprehensive understanding of the state-of-the-art ILEs for psychomotor training and provide a foundation for future research in this evolving field.

The orientation programs in most of the schools do not mitigate the diverse necessities of students. In addition, the instability of the labor market and the complexity of life have a great impact on young people’s career choices. Faced with these concerns, high school students get confused when choosing a college major. Furthermore, the explosion of data on the Internet has caused most of the Internet users to make possible unsuitable decisions when browsing the Web, due to their inability to handle such large amounts of data. In this paper, the Case-based reasoning, and Ontology-based Hybrid Recommender System (COHRS) is proposed to assist high school students deciding the appropriate university/college, university major and career domain that best fit their preferences. COHRS uniquely combines case-based reasoning, collaborative filtering, knowledge base and ontology to explore the top N recommendations based on their fields of interest. The system has been evaluated on Lebanese students through a real-life dataset collected from different Lebanese cities. The first tests carried out on 60 high school students in Beirut city showed an average satisfaction level of 91.7% of the recommended results from the proposed system and 93.3% of them found the system very useful. The proposed system achieved an average accuracy level of 98% and 95% to retrieve the most similar cases and to extract appropriate recommendations respectively, which provides a very insightful capability to guide high school students in their future directions.

For several decades, digital formative assessment tools and platforms have been promoted as promising for supporting adaptive teaching. For learning goals such as procedural fluency, this promise has been held across a range of subject-matter topics. For conceptual learning goals, however, the available digital formative assessment tools are much less widespread, and the research needed to develop them still seems to be underestimated. This paper reports on the design process of the Mastering Math Online-Check to illustrate approaches to a research-based design of targeted digital formative assessment tools that (a) are relevant, (b) are valid, and (c) provide in-depth, informative insights into students’ understanding of subject-matter concepts (in this case, basic arithmetic concepts such as the meaning of multiplication and division). The described research needs and the considerations about research-informed designs refer to improving the depth of insights into students’ understanding and their explanations of meanings. This conceptual (rather than empirical) paper discusses pivotal questions that must be addressed to fully leverage technological advances for the assessment of deep conceptual understanding, not only for mathematical concepts but also for other abstract concepts that rely on explanations and visual representations for the assessment of their understanding.

Augmented reality (AR) technology has risen as a promising instrument for enriching educational encounters across diverse learning environments. In the realm of English as a Foreign Language (EFL) instruction, AR applications have shown potential in improving vocabulary learning and retention among students. This research investigates the effect of the ARLOOPA augmented reality app on the countable and uncountable vocabulary learning and retention of EFL students at a high school level within the context of flipped instruction. The study focused on a cohort of 30 female EFL students, who were chosen based on their results in the Oxford Quick Placement Test. Prior to the intervention, a countable and uncountable vocabulary pretest was administered to assess the students' initial proficiency. Both the flipped online and flipped face-to-face groups received countable and uncountable vocabulary instruction using ARLOOPA augmented reality app. However, the flipped online group accessed the instructional materials through online platforms, while the flipped face-to-face group received them in traditional classroom settings. Following 12 sessions of the treatment, a follow-up assessment was carried out to evaluate the effects of the AR app on the students' countable and uncountable vocabulary proficiency. Additionally, a delayed vocabulary test was administered two weeks after the post-test to assess the participants' retention of the newly acquired countable and uncountable vocabulary. Analysis of the data indicated that the online flipped group performed better than the face-to-face flipped group. The findings suggest that the online instruction, coupled with the interactive and immersive nature of ARLOOPA, contributed to the enhanced countable and uncountable vocabulary learning outcomes in the flipped online group. These results underscore the potential of AR technology and flipped instruction in EFL classrooms, especially when delivered through online platforms, to create more engaging and effective learning environments.