Journal of Computing in Higher Education

Jacques Ellul, a 20th century French academic, is best known for his writing on technique, understood as both individual means to ends and an all-encompassing system that prioritizes efficient solutions to problems. While Ellul’s terminology is not necessarily familiar in contemporary educational technology research, it represents traditional understandings of individual tools as a subset of instructional systems and captures the field’s emphasis on finding more efficient and efficacious means of teaching and learning. However, Ellul’s writing on technique is largely skeptical, creating an opportunity for educational technology researchers to turn a more critical eye towards our emphasis on solutions to problems. This essay argues that while an increased emphasis problems over things is welcome, Ellul’s writing invites more careful consideration of what it means to solve problems. In particular, I draw on Ellul to ask three provocative questions: which problems should we solve, who should solve those problems, and is solving problems always good?

The educational technology field is at a critical juncture, facing the dual pressures of rapid technological advancement and a pressing need for research that genuinely addresses educational challenges. Despite increasing awareness of these issues, a significant amount of educational technology research remains entrenched in superficial or trend-driven inquiries, failing to tackle deeper, systemic issues. This paper critically examines the historical and institutional forces sustaining what we term “the research we don’t need,” and argues for a transformative shift toward “the research we need.” Such research must prioritize depth, long-term impact, and relevance over mere novelty or ease of publication. We outline how entrenched practices, including academic publishing standards, tenure and promotion metrics, and funding structures, contribute to a cycle that rewards superficial research. To disrupt this cycle, we propose actionable strategies to foster a research ecosystem that values substantive contributions and advocates for systemic change. Ultimately, we urge scholars, institutions, and professional organizations to embrace a collective responsibility to redefine research priorities holistically. By doing so, we can foster a field that meaningfully impacts educators, learners, and society. This is not merely a call for incremental improvements; it is a challenge to realign the field’s fundamental purpose toward more impactful, responsible, and enduring scholarship.

This study used both questionnaire and clickstream data to examine the relations between study approach, study time, and academic performance in low-stake and high-stake assessments in flipped classrooms. The questionnaire data identified two clusters of students reporting deep and surface study approaches. Students who reported a deep study approach performed better than those who reported a surface study approach on both low-stake and high-stake assessments. The clickstream data detected two clusters of students using either preparation-oriented or assessment-oriented approaches. Students who adopted preparation-oriented approach achieved higher on both low-stake and high-stake assessments. Students’ study time measured by both questionnaire data and clickstream data consistently contributed to both low-stake and high-stake assessments. However, the contributions of study approach to academic performance were not consistent across the two types of data, as self-reported study approach was only a significant predictor of high-stake but not low-stake assessment, suggesting that study approach measured by questionnaire data might not be sufficiently sensitive to detect variations in study approaches in flipped classrooms. Pedagogically, the results suggest that raising students’ awareness of the importance of pre-lecture learning and aligning assessments and learning activities may foster quality flipped classroom learning. Methodologically, the study demonstrates the advantages of combining questionnaire and clickstream data to understand students’ experiences of learning in flipped classrooms.

Despite the enormous investment in educational technology research, there are sincere questions about whether it is having a meaningful effect on issues that really matter. Put simply, is education better because of us? In this paper we argue that our field is not having the impact it could, due largely to our instrumentalist approach to ed tech research. Instrumentalism transforms the educational problems we study into little more than opportunities to efficiently deploy technologies and other resources that are presumed to optimize educational systems. But despite instrumentalism’s near-ubiquity, there is an alternative. By analyzing a case study of research characterized by researcher immersion and entanglement with the situation under study, we show how educational technology can resist the instrumentalist tendencies that reduce even the most serious problem into simply another resource to be optimized. In large part this occurs as we adopt practices that demand that we change ourselves—striving on our parts for more sensitivity, more understanding, more caring—so we are up to the task helping education become more just, more humane, and more focused on students’ existential development.

The goal of the present study was to map the available evidence and review the existing knowledge base on first-generation college students’ learning in online environments in hopes of pointing out future research directions for the scholarly community and providing implications for practitioners. To this end, a systematic search of electronic databases was conducted to select scholarly sources and grey literature related to online learning involving first-generation college students in higher education settings. The findings of the present review identified several extrinsic barriers that could influence first-generation college students’ success in online environments, such as financial constraints, multiple obligations, and lack of flexibility in course structures. In spite of the hurdles, first-generation college students were both intrinsically and extrinsically motivated to learn in online settings. Further, there was no evidence to show that first-generation college students were less capable of regulating their own learning in online learning environments than their peers. There was no conclusive evidence on the course withdrawal rate and degree completion between generation status, either. However, many studies indicated that first-generation college students who studied in online settings were less likely to perform well and stay in the programs than those who studied in face-to-face learning environments. The key to supporting first-generation college students’ learning in online environments is to create inclusive and welcoming learning contexts at course and school levels. Suggestions for future research and implications for online course and program design are discussed.

Gamification, which consists of incorporating elements of game design into non-game contexts, has been widely used in educational environments to increase students’ engagement. One such gamification strategy has used individual leaderboards, ranking students based on their performance in a particular task or activity such as a quiz. Most research has demonstrated a positive impact of leaderboards on various academic outcomes, and notably cognitive and behavioral engagement. However, as leaderboards are mostly based on competitive processes, they can be socially threatening and lead to a negative impact on social engagement for students who do not value competition, such as female students in psychology. The present study compared a ‘leaderboard’ condition based on performance on a series of quizzes to a ‘non-leaderboard’ condition among first-year female psychology students during a series of lectures. Results revealed that, independently of the students’ initial competitive orientation, exposure to a leaderboard led to lower social engagement with peers. No effects were found on other forms of engagement. An improvement in performance on quizzes from the first to the last lecture was also observed, independently of whether students were exposed to a leaderboard or not. These findings suggest that the potentially negative effects of leaderboards on students’ social engagement should be reconsidered taking into account differing student profiles regarding competition.

In this paper, the authors examine the complex relationship between education research and policymaking, analyzing key barriers and potential solutions for increasing research impact on policy. Four main challenges are identified: differing cultures and incentives between researchers and policymakers, communication barriers, competing values in decision-making, and the political nature of education policy. We posit that bridging research and policy is challenging but may be possible through research designs that consider implementation contexts, relationship building, policy-analytic approaches, and institutional support. We conclude with specific recommendations for expanding policy-related work and research in the field of educational technology as well as related translational work to facilitate better connections to policy and practice.

Exploring the factors that affect the intention to continue using MOOCs (ICM) has become an important topic, which attracted a widespread attention from scholars and practitioners. However, the previous researches have rarely considered the influence of “distance” on the ICM. Therefore based on the modified technology acceptance model, this paper proposed a new model by integrating the modified technology acceptance model and transactional distance theory to analyze the influence of “distance” on the ICM. A total of 256 samples were collected through both online and offline questionnaires. The PLS-SEM method and the software of Smart-PLS 3.0 was used to process the data. The results indicated that this model could explain 50.60% variance of the ICM. The transactional distance (interactivity) led to the ICM through the (chain) mediating role of perceived usefulness (PU), perceived ease of use (PEOU), and satisfaction. Moreover, the learner autonomy significantly moderated the relationship between transactional distance (interactivity) and PU, PEOU and satisfaction. This study provided a better understanding of the relationships among interactivity, learner autonomy, PU, PEOU, satisfaction and the ICM, which contributed to guide practitioners to better design MOOCs to improve the ICM.

One way to help frame a focus on problems instead of things is the Grand Challenges concept, which has been used in many other fields to date. Grand Challenges are an articulation of large-scale, complex problems that may be addressed through coordinated and sustained efforts but require long-term effort. Often, the articulation of Grand Challenges for a field can drive collaborations, grant funding through federal agencies and foundations, and provide a structure for research and publications around nodes of activities related to priority problems or needs. In this paper, I propose that the field of instructional design and technology (IDT) adopt a Grand Challenges initiative, provide examples from other fields, and provide examples of possible Grand Challenges in our field along with considerations and next steps for the IDT research, practice and policy community.

The flipped classroom approach involves restructuring traditional classroom instruction and facilitating students' active involvement with educational resources beyond the classroom setting. This approach allows for in-class activities that promote active learning and collaboration. The present study directed to investigate the influence of the flipped classroom on creative thinking, self-esteem, and social interaction among intermediate-level language learners. However, there has been limited discussion on this topic so far. In 2023, researchers employed a multi-stage cluster sampling technique to select participants. A total of 420 intermediate language learners from various institutions were randomly divided into an experimental group (210 learners) and a control group (210 learners). To ensure participant homogeneity, the Oxford placement test was used to assess the language proficiency of the learners. The research instruments included the Torrance creative thinking scale, the Rosenberg self-esteem scale, and the Garsham and Elliott social interaction scale. Descriptive and inferential statistics were employed to evaluate the data applying SPSS 25 and Amos 24 software. The findings from both descriptive and inferential analyses imply that the flipped classroom approach has a significant impact on creative thinking, self-esteem, and social interaction among English foreign language learners (EFLLs). Language educators are encouraged to adopt specific elements of this approach, such as structured pre-class activities (e.g., video lectures), interactive in-class discussions, and collaborative projects, to create engaging learning environments for EFLLs. Further research should explore the long-term effects of the flipped classroom on language retention and learner motivation, as well as its applicability across various proficiency levels, age groups, and cultural contexts.

As collaborative learning environments, forums in massive open online courses (MOOCs) seek to facilitate knowledge construction though meaningful discussions. Such discussions, however, rarely occur Problems such as difficult navigation, non-interactive participation, and brief interactions hinder discussions in MOOC forums. While pedagogical design holds promise for addressing these issues, few studies have implemented interventions to explore their impact. This paper presents findings from an intervention redesigning the forums in two MOOCs. Using a layered approach, we redesigned 12 forums to improve navigation, promote interactive participation, and increase the length of learners’ interactions. Results show that our intervention significantly reduced forum posts with uninformative titles, thereby improving navigation. Our intervention also helped learners both start and reply to threads, improving the quality of their forum interaction. Lastly, our intervention helped to increase the number of interactions, though interactions were not necessarily longer. These findings highlight the importance of pedagogical design in fostering meaningful discussions in MOOC forums.

Considering both the transformative opportunities and challenges presented by generative AI (GenAI) in academic writing, effectively integrating GenAI into the academic setting becomes a significant need requiring prioritization. Yet, there is limited understanding regarding the nature of interactions between different types of students, what behavioral patterns students exhibit during a student-GenAI interaction (SAI) on a given task, and how these different SAI patterns relate to the actual writing task performance. This study, therefore, aimed to identify SAI patterns of academic writing tasks depending on students’ level of AI literacy and examine the differences in academic writing performance between the identified SAI patterns. Drawing from the combination of three data sources, including think-aloud protocols, screen-recordings, and chat histories between 36 Chinese graduate students and a GenAI writing system, epistemic network analysis (ENA) was used to reveal the distinctive SAI patterns of students with different levels of AI literacy. The study found that students with a high level of AI literacy exhibited a collaborative approach to SAI, actively accepting GenAI’s suggestions and engaging GenAI in meta-cognitive-related activities such as planning, whereas students with a low level of AI literacy demonstrated much less interaction with GenAI in completing their writing tasks, instead choosing to ideate and evaluate independently. In addition, the Wilcoxon rank-sum (Mann-Whitney U) test was conducted to assess the writing task performance of the two AI literacy groups. Findings revealed statistical differences in all evaluation rubrics (content, structure/organization, expression). This study offers implications for the design and implementation of GenAI agents in writing tasks and the pedagogy of GenAI-assisted instruction.

Collaborative knowledge building (CKB) encourages students to build on knowledge at the group level through peer interactions. Process and summative assessments are essential methods for understanding and promoting the quality of CKB, but few studies focus on the assessment at the group level. To provide an operationalizable measurement of CKB process, this research conducted a process and summative assessment of Knowledge Forum data from groups of graduated students, then conducted group classification based on the assessments, and further examined the transitional and developmental characteristics. The research proposes an operationalizable measurement equation for assessing the quality of the CKB at the group level, it also proposes a summative assessment based on the final knowledge artefacts produced by the groups. Group classification was identified based on the results of both the process assessment and the summative assessment. Using the process mining method, this research visualized and demonstrated the procedural details of learning engagement within different group classifications during the CKB processes. The research identified four distinct group classifications based on the process assessment of CKB and the summative assessment of final research proposals. The results of process mining showed that four group classifications exhibited varying transitional and developmental processes in terms of social, cognitive, and metacognitive engagement. Results showed that the high-quality CKB process and performance primarily depended on progressive interactions based on group-level knowledge negotiation or perspective exchange, rather than merely interacting on questioning or information sharing. Three significant pedagogical implications and three assessment implications were proposed.

Collaborative learning is a fundamental skill based on the construction of knowledge through collaborative discussion in order to comprehend diverse perspectives. In online and flipped classrooms, which have become popular in higher education, learning interventions that provide a high level of collaborative cognitive support are required to increase active participation and enhance learning. At this point, there is a need to explain the contribution of socially shared metacognition (SSM) support for effective collaborative work in online and flipped classrooms. This study aims to investigate the effect of online and flipped classes supported by SSM on group metacognition (MCO), group belonging (GB), cohesion, and motivation. For this purpose, an experimental intervention consisting of two sub-studies was conducted with 330 university students. Descriptive statistics and partial least squares-structural equation modeling (PLS-SEM) analyses were employed in the analysis of the data. As a result of the research, when the pretest and posttest results were compared in the group provided with flipped SSM support, it was found that group belonging, metacognition, cohesion, and intrinsic and extrinsic motivation scores showed significant and positive development. In the online SSM-supported group, group cohesion (GC) showed a significant increase in the context of the pretest and posttest scores. In MGA analysis, it was concluded that the path coefficient differentiation of group metacognition was higher in those who received online SSM support. SSM support positively affected the perception of task difficulty in both flipped and online classes.

This study presents a scientometric analysis of educational technology research through examining highly cited articles published between 2014 and 2023 in 19 SSCI-indexed Q1 journals. Using a weighted approach to address citation bias, we analyzed 1,770 highly cited articles through document co-citation analysis, keyword analysis, and abstract content analysis. The findings reveal eight distinct research clusters, with Technology Acceptance Model, Computational Thinking, and Classroom Approach emerging as dominant clusters. The analysis identifies five major research themes, with AI-Enhanced Learning Technologies comprising 39% of the research focus, followed by equal distribution (17% each) among Virtual Learning Environments, Digital Learning Practices, and Learning Assessment & Feedback, while Educational Technology Integration accounts for 11%. Keyword analysis further indicates the field’s evolution toward more sophisticated technological applications such as virtual, online learning, and learning analytics emerging as prominent terms. This study demonstrates a significant transformation from basic technology integration to advanced AI-driven solutions. The findings provide valuable insights for researchers and practitioners in educational technology, suggesting future research directions should focus on AI integration, immersive technologies, and data-driven approaches while maintaining emphasis on pedagogical effectiveness and student engagement.

Abstract

The use of ill-structured case examples as an instructional strategy to teach ethical lessons is well-supported in the literature, however, case examples often lack an emotional or affective component. Given the importance of crafting cases for learners, more research is needed to better understand how to construct and present case examples to enhance learning outcomes, specifically related to the influence of emotive content. This study was conducted to assess the effect of emotive content on knowledge acquisition and ethical sense-making. The study employed a posttest-only control group design. Emotive content was defined as information related to the character’s emotional reactions or feelings, background, beliefs, physical appearance, and/or goal focus of the character. Participants were 71 graduate-level Master of Social Work students at a university in the coastal U.S. Results contribute to the growing body of literature regarding the effect of emotion in processing and manipulating complex information. The results suggest that the addition of emotive content to a case example may distract or overwhelm learners. Case examples should be constructed using clear and simple information.

To meet the demands of 21st-century societies and economies, faculty across disciplines must engage college and university students with course activities and assignments that foster the development of computational thinking (CT) skills. Toward this end, examining the ways in which CT can be infused into general education courses has been a topic of recent research. However, the question remains about how students in non-computer science courses can use CT skills in course assignments across disciplines. Guided by a rubric aimed to evaluate the development of CT skills including decomposition, algorithms, data, and abstraction, we examined 101 student-generated artifacts in undergraduate courses across four disciplines: mathematics, sociology, music, and English. In this work, we report on assignment prompts and overall CT skills exhibited by participating students. While some disciplines may not fully facilitate the development of all CT skills, a range of these skills was reflected in student artifacts. We present representative examples demonstrating CT skill development across various levels, including capstone level (score 4), milestone (score 3), benchmark (score 1), and no usage (score 0). The findings of this work provide insights into ways in which higher education faculty can design assignment prompts that support and scaffold students’ development of CT skills, as well as how students across disciplines respond to CT prompts. Findings also have implications for the design of CT-related assessment instruments.

Given the importance of self-regulated learning (SRL) in flipped learning in higher education, this study explored the role of a mobile-based artificial intelligence (AI) chatbot in enhancing SRL among university students enrolled in a flipped business course. The chatbot supported students by providing SRL prompts in the forethought, performance, and reflection phases. An explanatory sequential mixed-methods design was employed to examine the effectiveness of the chatbot and students’ conversation patterns. Survey data from 43 participants revealed that low prior-SRL students significantly benefited from chatbot interaction, while high prior-SRL students surprisingly exhibited a decrease in their SRL scores. Qualitative analysis of extreme cases revealed evident differences in interaction patterns between students whose SRL scores decreased and increased after chatbot use. The findings contribute valuable insights to the expanding field of mobile-based AI chatbots in flipped learning and emphasize the importance of adaptive and personalized interventions for students according to their prior SRL skills.

Flexible online distance education enables students to interact with content and materials at their own pace and from any location. However, such individualization of students’ learning time and space masks differences between learners’ access to resources within their spatial environments and temporal contexts and, thus, might generate implicit forms of social inequity. This study examines how flexibility inherent to emergency remote online learning shapes how Israeli university students from different social groups experienced remote online learning during the Covid-19 pandemic. We thematically analyzed semi-structured interviews with 50 undergraduate and graduate students, representing diversity in terms of class, gender, and national categories. We found four spatial and temporal factors that shaped students’ ability to harness flexibility to benefit their emergency remote online learning: spatial capital, temporal capital, temporal agency, and temporal intensity. The analysis revealed how such factors were shaped by complex intersections between students’ social identities. This study suggests that higher education institutions should make flexibility inclusive and safeguard students from potential adverse effects by tailoring support to diverse student needs and ensuring consistent access to resources as needed.

This study fills a gap in knowledge regarding experienced instructors’ use of learning analytics, focusing on differences in their approach, the knowledge and skills they activate, and the development of these knowledge and skills. Through a qualitative analysis of think-aloud interviews with 13 analytics-experienced instructors, two distinct profiles of analytics use emerged. Instructors in the first profile prioritized monitoring student engagement and performance to foster desirable behaviors, using analytics to align students with course expectations. Instructors in the second profile focused on understanding student perceptions of learning, aligning the course design with diverse learning behaviors and needs. To arrive at such use, instructors went beyond mere acquisition of technical knowledge to also integrate pedagogical knowledge into their analytics practices. Lastly, the study uncovered specific learning analytics supports, such as ongoing individual consultations, invaluable for developing the needed technical and pedagogical knowledge. Together, the results of this study reveal the pivotal role of pedagogy in analytics use, calling for refinement of conceptual models and tailoring of practical support for instructors.