Computers and Education: Artificial Intelligence
Monday, October 5
Towards a new AI-TPACK framework: Evidence from China
This study examines the development of teachers’ AI-integrated teaching competence, defined as AI-Technological Pedagogical Content Knowledge (AI-TPACK), aiming to move beyond additive assumptions toward an ethically grounded model. Based on survey data from 454 Chinese university teachers, a suppression pattern…
doi.org
Thursday, October 1
Response-length confounding in participant–morpheme networks: A length-controlled test in AI ethics education
Background. Equipping learners with AI-ethical literacy is a priority for higher education, yet item-level self-reports leave two observables unrecorded: the structure of lexical co-use in learners’ written responses and the polarity of their free text. Neither is a measure of learning. A further inferential hazard is…
doi.orgModeling the Relationships Between University Students’ AI Competence, AI Ethical Awareness, and AI Anxiety: A Dual-Stage PLS-SEM and ANN Analysis
AI anxiety is increasingly prevalent among university students, yet mainstream AI literacy interventions are often infeasible in resource-constrained settings. This study focuses on a law-dominant university in western China, where AI literacy education is absent. Students’ AI competence and AI ethical awareness are…
doi.org
Wednesday, September 23
Generative AI-assisted workflows in architectural conceptual design: Performance, creative self-efficacy, and cognitive load
Generative AI (GenAI) is increasingly adopted in design education, yet evaluating its educational value through final outcomes provides an incomplete picture. This study compares two ecologically plausible workflows in an architectural conceptual design task: GenAI-assisted image generation and ArchDaily-based…
doi.org
Tuesday, September 22
Agentivism: a learning theory for the age of artificial intelligence
Learning theories have historically changed when the conditions of learning evolved. Generative and agentic AI create a new condition by allowing learners to delegate explanation, writing, problem solving, and other cognitive work to systems that can generate, recommend, and sometimes act on the learner’s behalf. This…
doi.orgA mixed-methods analysis of AI scaffolding patterns and student inquiry profiles in a middle-school agriculture-STEM classroom
This study examines how generative AI can support middle school scientific inquiry in a rural agriculture-STEM classroom. Using a mixed-methods design with concurrent data collection and sequential analytic integration, we analyzed 42 eighth-grade students, organized into 12 groups, as they used Aspen, a custom AI…
doi.org
Friday, September 18
Building AI companions that prioritise learning over performance
Generative AI, currently most visible in education through large language models (LLMs), is increasingly embedded in students’ everyday learning practices, supporting tasks such as writing, coding, reasoning, and analysis. Yet their educational value remains uncertain because systems designed to improve immediate task…
doi.orgChatGPT for interdisciplinary learning: Does it equally benefit STEM and non-STEM students
While studies on using generative AI for education are increasing, research on whether it benefits STEM and non-STEM students, who tend to have different technology acceptance and AI literacy, in the interdisciplinary learning context is rare. To respond to this gap, this exploratory quasi-experiment study engaged 130…
doi.org
Wednesday, September 16
A hybrid collaborative filtering and knowledge graph-based cross-domain recommendation method for multimodal teaching resources
This paper proposes a hybrid recommendation system that integrates collaborative filtering with a pedagogically structured knowledge graph for personalized multimodal English learning resource recommendation. Resources, concepts, and learner attributes are organized into four instructional dimensions, and…
doi.org
Thursday, September 10
Wednesday, September 9
AI-mediated research agency formation in higher education: Autonomy, self-efficacy and innovation in early-career scientific training
Generative AI is becoming part of the infrastructure of higher education research training, yet little is known about how AI-mediated environments shape early-career researchers’ agency. This study examines AI dependence, defined as reliance on intelligent tools as a primary source of cognitive support in…
doi.org
Thursday, September 3
When the algorithm enters the classroom: A critical integrative review of large language models, nursing education structural gaps, and the reconstitution of professional identity
Large language models (LLMs) are being integrated into nursing education at a pace that outstrips the field’s capacity to evaluate their consequences. Existing syntheses have mapped what LLMs can do in nursing contexts. Among those identified in this review, none has examined how their integration affects the…
doi.org
Saturday, August 22
Bridging the domain gap for VLMs: A scientific fine-tuning framework for precision and pedagogy in astronomical image understanding
Vision-language models (VLMs) hold significant potential for educational applications; however, existing research has predominantly relied on the direct invocation of general-purpose architectures, lacking systematic fine-tuning methodologies tailored to discipline-specific visual corpora. This study situates its…
doi.orgA hybrid reasoning framework for artificial intelligence assessment rubric generation in human and automated contexts: Evidence from an undergraduate programming course
Developing assessment rubrics is resource-intensive, limiting frequent formative assessment. This study introduces HARMOGEN-R (Hybrid Assessment Rubric Model Generation with Reasoning), a framework that uses reasoning-enhanced Large Language Models (LLMs) for initial rubric generation and standard models for…
doi.org
Friday, August 21
Preferred scaffolding does not lead to better learning performance: Empirical evidence from AI-supported mathematical modelling
Mathematical modelling (MM) is widely recognized as a key competency for addressing complex real-world problems, which requires learners to engage in higher-order processes such as abstraction, representation, and iterative reasoning. However, students often experience difficulties in coordinating these processes…
doi.orgReconceptualizing community of inquiry in the age of generative artificial intelligence
The Community of Inquiry (CoI) framework is widely used to guide and explain learning in online and blended environments. However, generative artificial intelligence (GenAI) challenges a key assumption in CoI research and practice: that indicators of presence can be attributed primarily to human learners, instructors,…
doi.org
Wednesday, August 19
Applying psychometric methods to distinguish between human and generative AI responses to multiple-choice assessments
The growing use of generative AI (GenAI) tools like ChatGPT raises serious concerns about academic integrity, especially in the context of assessments. While detection efforts have focused on open-ended responses, multiple-choice questions (MCQs), which are common in high-stakes testing, remain largely overlooked,…
doi.orgAI-mediated cognitive divergence in built-environment education: Evidence from a mixed-methods study
Generative artificial intelligence (AI) is rapidly integrating into design education, yet its effects on student learning processes remain empirically underexplored. This study reports a sequential mixed-methods investigation across a built-environment faculty at a research-intensive university, drawing on 24 faculty…
doi.org
Tuesday, August 18
Teachers as reflective regulators of cognition: Understanding cognitive offloading in AI-augmented practice
This study investigates how teachers perceive, manage, and reflect on the cognitive implications of integrating Generative Artificial Intelligence (GenAI) into their professional practice with a focus on the evolving interplay between human judgment and automation. Using a collective case-study design, we conducted…
doi.org
Sunday, August 16
Automatic discourse relation classification and feedback optimization in English teaching based on transformer BERT model
To address the limitations of existing automatic evaluation systems that rely on surface features and fail to provide actionable feedback for improving discourse coherence, we propose a Transformer model based on BERT to classify discourse relations (causal, contrastive, progressive, or incoherent) between adjacent…
doi.org
Friday, August 14
LLMs do not grade essays like humans
Large language models have recently been proposed as tools for automated essay scoring, but their agreement with human grading remains unclear. In this work, we evaluate how LLM-generated scores compare with human grades and analyze the grading behavior of several models from the GPT and Llama families in an…
doi.orgThe IDEA framework for metacognitively regulated GenAI use in higher education: Development and exploratory pilot evidence
Generative artificial intelligence (GenAI) can enhance students’ efficiency and the apparent quality of academic work, yet its fluent outputs may encourage learners to outsource cognitive activities central to learning. This creates the risk of “performance without learning”, whereby successful task completion does…
doi.org
Monday, August 10
Not for people like me: How frontier AI models redirect skeptical rural school staff
doi.orgNeuro-symbolic pedagogical alignment (NSPA) for long-horizon classroom discourse analysis: Mitigating dialect bias via counterfactual preference optimization
Automated analysis of classroom discourse has traditionally relied on discriminative Transformer architectures like RoBERTa to classify isolated utterances, an approach that inherently struggles with long-horizon dependencies and exhibits significant algorithmic bias against speakers of non-standard dialects of…
doi.org
Friday, August 7
Federated learning for privacy-preserving at-risk student prediction in health professional education: A multi-scenario evaluation of FedAvg and FedProx
Student attrition in health professional education (HPE) carries serious implications for institutional performance and healthcare workforce supply, yet cross-institutional prediction is impeded by privacy regulations that prevent raw data sharing. This study presents, to the best of the authors' knowledge, the first…
doi.org
Sunday, August 2
Standardized assessment of LLM English proficiency
Large language models (LLMs) are increasingly used in language learning and assessment, yet their English proficiency is seldom reported against interpretable proficiency standards. We introduce the China’s Standards of English Language Ability (CSE) framework to assess the proficiency levels and subskills of LLMs.…
doi.org
Saturday, August 1
Thursday, July 30
The agency gap in AI-supported writing: How reactive and proactive agent designs shape multimodal reasoning
Generative AI is becoming part of academic writing, but its educational value depends on how control is shared between learner and system. This study examined an agency gap : performance differences that may arise when AI agent initiative is misaligned with learners’ generative AI literacy. Seventy-nine medical and…
doi.org
Wednesday, July 29
A scoping review of generative AI-powered agentic AI in education: Research landscape, agentic capabilities, and insights from the frontier agent paradigm, exemplified by OpenClaw
Generative AI-powered agentic systems are increasingly proposed for educational applications. However, the research landscape remains fragmented, and the relationship between technical capabilities and pedagogical design remains poorly understood. To address this gap, this scoping review systematically mapped 474…
doi.org
Monday, July 27
From simulation to flight: Simulation-assisted drone learning with teacher-AI co-designed scaffolds for secondary students’ STEM knowledge and competencies
A persistent challenge in drone-based STEM education is the scarcity of teacher-verified, interactive simulations that support both conceptual learning and competency development. Generative AI can accelerate content creation, but its outputs frequently lack pedagogical validity and contextual alignment. This study…
doi.orgArtificial intelligence ethical awareness of university students in Ghana: A network and latent profile analyses
Artificial intelligence is becoming increasingly integrated into students’ academic lives in Ghana, making it crucial to examine their perspectives on ethical dimensions. Against this backdrop, this study assesses the artificial intelligence ethical awareness (AIEA) among 509 Ghanaian university students across the…
doi.org
Saturday, July 25
Chat as learning: Student–AI conversations as discipline-associated cognitive engagement patterns
Generative AI teaching assistants are increasingly adopted in higher education, yet debates persist over whether student–AI conversations engage students in genuine cognitive processes or function primarily as information retrieval. We propose “Chat as Learning,” a measurement paradigm that treats student prompts as…
doi.org
Thursday, July 23
A socio-technical framework for educational excellence: Empirical validation of artificial intelligence and Jidoka integration in accounting pedagogy within emerging financial markets
The focus of this research is on how AI instrumentation affects quality-assurance systems based on the concept of Jidoka within the ecosystem of accounting education in an emerging financial-market environment. The study fills a void regarding technology use beyond traditional financial-center locations by addressing…
doi.org
Wednesday, July 22
In the AI era: A project-based digital storytelling framework for art and design education
The ascent of generative artificial intelligence (AI) challenges art and design education to reaffirm the value of human creativity. This study proposes and examines a pedagogical response: a project-based learning (PBL) model with digital storytelling (DS) at its core, designed to cultivate the emotional, cultural,…
doi.org
Monday, July 20
AI adoption readiness among Ukrainian education managers: Barriers, typologies, and policy implications
Artificial intelligence (AI) adoption in education requires strategic leadership from education managers, yet little research examines AI readiness among this stakeholder group, particularly in post-Soviet transitional contexts. As decision-makers who control whether and how AI enters educational practice, managers’…
doi.orgVETTING: A dual-LLM framework for in-loop safety verification via policy isolation in educational AI
Educational AI systems increasingly rely on large language models to support student writing and inquiry, yet enforcing safety and instructional constraints during open-ended, multi-turn interaction remains challenging. Existing approaches commonly embed such constraints within conversational prompts or rely on static…
doi.org
Friday, July 17
Comparing human and LLM ordered coding of qualitative data: How coding differences cascade through temporal analysis
Automating the process of qualitatively coding text data from learners has been a long-standing ambition of learning analytics researchers since it represents an essential step toward delivering timely and scalable feedback. Automating this process is especially challenging in the case of ordered coding schemes…
doi.orgAI literacy-related domains and AI-TPACK readiness among preservice mathematics teachers: A factor-informed structural equation modelling study
In this factor-informed exploratory CFA/SEM study, AI-literacy-related domains were treated as theoretically informed and empirically tested predictors of AI-TPACK readiness rather than as fully validated independent latent variables. Artificial intelligence (AI) is increasingly entering mathematics education, making…
doi.org