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Rune Johan Krumsvik – Education and Information Technologies, 2025
This exploratory case study examines how AI technologies, specifically a GPT-4-based synopsis chatbot, can serve as a sparring partner for doctoral students in Norway. Despite favourable conditions, only two-thirds of Norwegian PhD candidates complete their doctorates, partly due to challenges with article-based dissertations that require a…
Descriptors: Doctoral Students, Artificial Intelligence, Academic Language, Computer Uses in Education
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Nasrin Dehbozorgi; Mourya Teja Kunuku – IEEE Transactions on Education, 2024
Contribution: An AI model for speech emotion recognition (SER) in the educational domain to analyze the correlation between students' emotions, discussed topics in teams, and academic performance. Background: Research suggests that positive emotions are associated with better academic performance. On the other hand, negative emotions have a…
Descriptors: Interaction, Academic Achievement, Artificial Intelligence, Psychological Patterns
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Lu, Chunyan; Minneyfield, Aarren; Jia, Min; Lu, Jun; Zheng, Yan; Huo, Jingying; Wang, Ningyi; Wu, Yihua; Brantley, Jennifer – Journal of Workplace Learning, 2023
Purpose: The purpose of this paper is to explore more agile and effective learning processes that help identify potentially high-performing staff during workplace training. Design/methodology/approach: To test the efficacy of the learning-oriented assessment (LOA) process in workplace training, a pharmaceutical sales organization implemented an…
Descriptors: Workplace Learning, Job Training, Learning Processes, Artificial Intelligence
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Elisabeth Bauer; Michael Sailer; Frank Niklas; Samuel Greiff; Sven Sarbu-Rothsching; Jan M. Zottmann; Jan Kiesewetter; Matthias Stadler; Martin R. Fischer; Tina Seidel; Detlef Urhahne; Maximilian Sailer; Frank Fischer – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence, particularly natural language processing (NLP), enables automating the formative assessment of written task solutions to provide adaptive feedback automatically. A laboratory study found that, compared with static feedback (an expert solution), adaptive feedback automated through artificial neural networks…
Descriptors: Artificial Intelligence, Feedback (Response), Computer Simulation, Natural Language Processing
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Steffen Steinert; Karina E. Avila; Stefan Ruzika; Jochen Kuhn; Stefan Küchemann – Smart Learning Environments, 2024
Effectively supporting students in mastering all facets of self-regulated learning is a central aim of teachers and educational researchers. Prior research could demonstrate that formative feedback is an effective way to support students during self-regulated learning. In this light, we propose the application of Large Language Models (LLMs) to…
Descriptors: Formative Evaluation, Feedback (Response), Natural Language Processing, Artificial Intelligence
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Adelina Asmawi; Md. Saiful Alam – Discover Education, 2025
In the evolving techno-educational landscape, it is crucial to reimagine transformative pedagogies based on techno-teacher collaboration to revolutionize teaching effectiveness and efficiency. Although the cutting-edge generative AI tool, Chat GPT, is speculated to be a revolutionary CALL (computer-assisted language learning) tool for teaching…
Descriptors: Reading Instruction, Teaching Methods, Computer Assisted Instruction, Instructional Effectiveness
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Marrone, Rebecca; Cropley, David H.; Wang, Z. – Creativity Research Journal, 2023
Creativity is now accepted as a core 21st-century competency and is increasingly an explicit part of school curricula around the world. Therefore, the ability to assess creativity for both formative and summative purposes is vital. However, the "fitness-for-purpose" of creativity tests has recently come under scrutiny. Current creativity…
Descriptors: Automation, Evaluation Methods, Creative Thinking, Mathematics Education
Jessica Kahlow – Online Submission, 2024
This comprehensive guide illuminates the art and science of educational assessment, blending ancient alchemical wisdom with modern AI innovations. Part one lays the foundation, exploring essential principles of assessment and evaluation and its pivotal role in shaping learning outcomes. Part two delves into diverse assessment types, from formative…
Descriptors: Educational Assessment, Student Evaluation, Educational Innovation, Artificial Intelligence
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Florian Weber; Thiemo Wambsganss; Matthias Söllner – British Journal of Educational Technology, 2025
Recent developments in artificial intelligence (AI) have significantly influenced educational technologies, reshaping the teaching and learning landscape. However, the notion of fully automating the teaching process remains contentious. This paper explores the concept of hybrid intelligence (HI), which emphasizes the synergistic collaboration…
Descriptors: Legal Education (Professions), Writing Skills, Skill Development, Feedback (Response)
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Catherine Nickerson; Peter Davidson – Business and Professional Communication Quarterly, 2024
In this discussion, we consider how the use of scenario-based assessment (SBA) can provide students with a way of developing the digital communication skills that business communication research has found they will need for the workplace, alongside other aspects of professional competence. This is because SBA can be employed to engage learners in…
Descriptors: Vignettes, Student Evaluation, Digital Literacy, Skill Development
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Ariely, Moriah; Nazaretsky, Tanya; Alexandron, Giora – International Journal of Artificial Intelligence in Education, 2023
Machine learning algorithms that automatically score scientific explanations can be used to measure students' conceptual understanding, identify gaps in their reasoning, and provide them with timely and individualized feedback. This paper presents the results of a study that uses Hebrew NLP to automatically score student explanations in Biology…
Descriptors: Artificial Intelligence, Algorithms, Natural Language Processing, Hebrew
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Gerd Kortemeyer – Physical Review Physics Education Research, 2023
Solving problems is crucial for learning physics, and not only final solutions but also their derivations are important. Grading these derivations is labor intensive, as it generally involves human evaluation of handwritten work. AI tools have not been an alternative, since even for short answers, they needed specific training for each problem or…
Descriptors: Artificial Intelligence, Problem Solving, Physics, Introductory Courses
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Yaw Marfo Missah; Fuseini Inusah; Ussiph Najim; Frimpong Twum – SAGE Open, 2023
The major challenge of most basic schools is inadequate educational resources despite a conscious effort to constantly provide. This is a result of inaccurate data management leading to inappropriate predictions for effective planning. The actual efficiency of a system is determined by its ability to predict real-life data with speed and accuracy.…
Descriptors: Mathematical Models, Information Management, Educational Resources, Artificial Intelligence
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Martin, Paul P.; Graulich, Nicole – Chemistry Education Research and Practice, 2023
In chemistry, reasoning about the underlying mechanisms of observed phenomena lies at the core of scientific practices. The process of uncovering, analyzing, and interpreting mechanisms for explanations and predictions requires a specific kind of reasoning: mechanistic reasoning. Several frameworks have already been developed that capture the…
Descriptors: Artificial Intelligence, Critical Thinking, Logical Thinking, Student Evaluation
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Jiseung Yoo; Jisun Park; Minsu Ha; Chelcea Mae Lagmay Darang – SAGE Open, 2024
In the context of formative assessment in classrooms, the incorporation of automated evaluation (AE) systems and teachers' interactions with them hold significant importance. This study aimed to investigate the cognitive processes of pre-service teachers as they engaged with an AE system. We developed an unsupervised learning-based AE system, the…
Descriptors: Preservice Teachers, Cognitive Processes, Automation, Supervision
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