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Open research questions in Online Learning and Analytics

1,253 gap statements mined from Online Learning and Analytics papers in our 7.9M-paper local library, which holds 4,087 papers on the topic — drawn mostly from each paper's own stated research gap, future-work, challenge and limitation notes, and its abstract. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one.

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What the literature leaves open

  • The need to identify informative predictors from a large set of LMS engagement indicators. The challenge of maintaining or improving predictive performance while reducing the predictor space.

    A Hybrid ACO–Ensemble Learning Framework for Predicting Student Forum Consumption Behaviour · 2026 · DOI

  • There is a lack of studies examining the impact of GenAI on academic information resource use. The study addresses the gap by using a convergent triangulation design.

    Generative artificial intelligence reshapes university students' sustainable use of academic information resources: mixed evidence from behavioral logs and perceptual survey data · 2026 · DOI

  • One challenge is the potential for selection effects in the analysis. Another challenge is the need to consider the impact of data minimization on predictive performance across different educational stages and review capacities. The study also faces the challenge of evaluating the effectiveness of early-warning systems in real-world educational settings.

    Evaluating Data-Minimized Early-Warning Systems for Educator Decision Support: Evidence Across Review Capacities and Educational Stages · 2026 · DOI

  • The gap in current research is the lack of understanding of how removing background information affects early-warning system performance. There is a need to evaluate data minimization at the intended educational stage and review capacity.

    Evaluating Data-Minimized Early-Warning Systems for Educator Decision Support: Evidence Across Review Capacities and Educational Stages · 2026 · DOI

  • The study highlights the need for developmentally appropriate instructional interventions for DTs and broader AI concepts.

    Unplugged Activities for Teaching Decision Trees to Secondary Students—A Case Study Analysis Using the SOLO Taxonomy · 2025 · DOI

  • Empirical evidence suggests that students frequently lack comprehensive understanding of underlying AI concepts. There is a need for systematic research initiatives addressing ML pedagogical methodologies. The study identifies a gap in the development of educational materials and methodologies to facilitate ML instruction within secondary education contexts.

    Unplugged Activities for Teaching Decision Trees to Secondary Students—A Case Study Analysis Using the SOLO Taxonomy · 2025 · DOI

  • The need to adapt to the transition towards a digital society and cultivate students' AI literacy. The complexity of elucidating the relationships among AI technology, pedagogical methods, and subject-specific content in education.

    Teachers’ AI-TPACK: Exploring the Relationship between Knowledge Elements · 2024 · DOI

  • The existing literature on the use of GenAI tools in education does not fully address the integration of GenAI tools with experiential learning for authentic assessment. There is a need to clarify and integrate the concepts of experiential learning and authentic assessment with GenAI tools.

    Using Generative Artificial Intelligence Tools to Explain and Enhance Experiential Learning for Authentic Assessment · 2024 · DOI

  • There is a relative scarcity of empirical studies that integrate large language models into classroom settings. The literature on the use of large language models in lesson creation features only a handful of examples. The reception and effectiveness of AI-generated virtual instructors remains unclear.

    Generative AI for Customizable Learning Experiences · 2024 · DOI

  • The study identifies the challenge of balancing the benefits of ChatGPT with the need for human-teacher interactivity and empathy. The study highlights the concern about accuracy and overreliance on ChatGPT. The study notes the challenge of integrating GenAI tools into EAP curricula in a way that supports students' autonomy and competence.

    The Impact of ChatGPT on English for Academic Purposes (EAP) Students’ Language Learning Experience: A Self-Determination Theory Perspective · 2024 · DOI

  • There is a lack of research examining the motivational aspects of students' engagement with generative AI tools like ChatGPT. The study aims to address this gap by exploring how ChatGPT impacts EAP students' basic psychological needs for autonomy, competence, and relatedness.

    The Impact of ChatGPT on English for Academic Purposes (EAP) Students’ Language Learning Experience: A Self-Determination Theory Perspective · 2024 · DOI

  • Future studies should use longitudinal designs to track changes in educators' perceptions, attitudes, and use of Gen AI tools over time. Comparative Studies: Conducting comparative studies across different regions, educational levels, and cultural contexts could help to identify universal and context-specific factors influencing Gen AI adoption.

    University Teachers’ Views on the Adoption and Integration of Generative AI Tools for Student Assessment in Higher Education · 2024 · DOI

  • The study highlights the need for targeted professional development and ethical criteria for the proper integration of Gen AI in educational assessment. The study seeks to address the concerns regarding the validity of assessments and the potential negative impact on students' writing and thinking skills.

    University Teachers’ Views on the Adoption and Integration of Generative AI Tools for Student Assessment in Higher Education · 2024 · DOI

  • The study identifies the challenge of excessive reliance on AI, which can lead to detrimental dependencies and hinder the development of essential 21st-century skills. The research notes the complexity of interactions between AI literacy, trust, and 21st-century skills. The study highlights the need for careful integration of AI technologies in educational settings.

    Latent Profile Analysis of AI Literacy and Trust in Mathematics Teachers and Their Relations with AI Dependency and 21st-Century Skills · 2024 · DOI

  • It notes the complexity of GenAI and the need for educators to develop AI literacy to effectively integrate it into their teaching practices.

    Modeling Teachers’ Acceptance of Generative Artificial Intelligence Use in Higher Education: The Role of AI Literacy, Intelligent TPACK, and Perceived Trust · 2024 · DOI

  • The lack of comprehensive analysis of the current academic discourse on AI tools in education. The need to identify the potential benefits and challenges related to ChatGPT use in educational settings. The necessity to summarize the utilizations of ChatGPT in teaching and learning by addressing the identified benefits and challenges.

    ChatGPT in Teaching and Learning: A Systematic Review · 2024 · DOI

  • The study notes that the articles that were not accessible at the time of retrieval might contain critical empirical evidence needed for this review. The study did not consider other databases and indexes, such as WOS, and it used only literature from SCOPUS. The themes studied are inextricably linked, making it difficult at times to differentiate the findings.

    Educational Approaches with AΙ in Primary School Settings: A Systematic Review of the Literature Available in Scopus · 2024 · DOI

  • The paper identifies the need for a comprehensive understanding of the current state and future prospects of learning analytics in higher education. The paper highlights the challenges of incorporating learning analytics into higher education, including data privacy concerns and algorithmic errors.

    The Evolving Classroom: How Learning Analytics Is Shaping the Future of Education and Feedback Mechanisms · 2024 · DOI

  • There is a research gap in investigating how teachers use various features of an AI-enabled system. The gap exists in understanding teachers' perceptions of AI integration in teaching to promote effective AI integration practices. The study aims to address this gap by exploring how six science teachers utilize an AI-enabled system.

    Investigating Teachers’ Use of an AI-Enabled System and Their Perceptions of AI Integration in Science Classrooms: A Case Study · 2024 · DOI

  • Investigate the long-term effects of GenAI on academic information resource use, - Examine the impact of GenAI on different types of academic tasks and resources, - Explore the role of task-channel fit in moderating the association between auxiliary GenAI use and continuance intention toward digital…

    Generative artificial intelligence reshapes university students' sustainable use of academic information resources: mixed evidence from behavioral logs and perceptual survey data · 2026 · DOI

  • The lack of interdisciplinary analysis of MOOC courses on heritage education, - The need for a metalinguistic approach to examine the semantic limits of emerging lexical categories, - The gap in understanding how participatory methodologies can shift perceptions…

    MOOCs in Heritage Education: Content Analysis and Didactic Strategies for Heritage Conceptualization · 2025 · DOI

  • Data privacy concerns and security. Algorithmic bias and ensuring fairness. Bridging the digital gap and promoting accessibility. Providing enough faculty training and uptake.

    The Impact of AI and LMS Integration on the Future of Higher Education: Opportunities, Challenges, and Strategies for Transformation · 2024 · DOI

  • Further studies on the impact of AI literacy on GenAI acceptance, - Investigations into the effects of targeted professional development initiatives on educators' confidence in using…

    Modeling Teachers’ Acceptance of Generative Artificial Intelligence Use in Higher Education: The Role of AI Literacy, Intelligent TPACK, and Perceived Trust · 2024 · DOI

  • A theoretical framework and/or policy guidelines for successful AI implementation in educational settings could be developed - Examine the effectiveness of AI implementation in terms of pedagogical strategies and learning outcomes according to the student's…

    Educational Approaches with AΙ in Primary School Settings: A Systematic Review of the Literature Available in Scopus · 2024 · DOI

  • The Inq-ITS is limited in effectively facilitating students with low English…

    Investigating Teachers’ Use of an AI-Enabled System and Their Perceptions of AI Integration in Science Classrooms: A Case Study · 2024 · DOI

Most-cited papers in Online Learning and Analytics

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Open questions raised by papers listed on this page include: (1) There is a lack of studies examining the impact of GenAI on academic information resource use (“Generative artificial intelligence reshapes university students' sustainable…”, 2026); (2) The gap in current research is the lack of understanding of how removing background information affects early-warning system performance (“Evaluating Data-Minimized Early-Warning Systems for Educator Decision Support:…”, 2026); (3) There is a need for systematic research initiatives addressing ML pedagogical methodologies (“Unplugged Activities for Teaching Decision Trees to Secondary Students—A Case…”, 2025); (4) There is a need to clarify and integrate the concepts of experiential learning and authentic assessment with GenAI tools (“Using Generative Artificial Intelligence Tools to Explain and Enhance…”, 2024); (5) The reception and effectiveness of AI-generated virtual instructors remains unclear (“Generative AI for Customizable Learning Experiences”, 2024). 1,253 gap statements have been mined from Online Learning and Analytics papers in our 7.9M-paper local library, which holds 4,087 papers on the topic; the gaps come from whichever of those papers state one. They are mostly the research gaps the authors state and the papers' abstracts, plus future-work, limitations and challenges passages. The ones listed below are a selection still marked open; each names the study that raised it, with a DOI link where the paper has one, so you can read the original claim in context.

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