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Direct linkElvis Ortega-Ochoa; Marta Arguedas; Thanasis Daradoumis – British Journal of Educational Technology, 2024
Artificial intelligence (AI) and natural language processing technologies have fuelled the growth of Pedagogical Conversational Agents (PCAs) with empathic conversational capabilities. However, no systematic literature review has explored the intersection between conversational agents, education and emotion. Therefore, this study aimed to outline…
Descriptors: Empathy, Artificial Intelligence, Databases, Dialogs (Language)
Markus Wolfgang Hermann Spitzer; Miguel Ruiz-Garcia; Korbinian Moeller – British Journal of Educational Technology, 2025
Research on fostering learning about percentages within intelligent tutoring systems (ITSs) is limited. Additionally, there is a lack of data-driven approaches for improving the design of ITS to facilitate learning about percentages. To address these gaps, we first investigated whether students' understanding of basic mathematical skills (eg,…
Descriptors: Mathematics Skills, Fractions, Prediction, Mathematical Concepts
Daryn A. Dever; Megan D. Wiedbusch; Sarah M. Romero; Roger Azevedo – British Journal of Educational Technology, 2024
Intelligent tutoring systems (ITSs) incorporate pedagogical agents (PAs) to scaffold learners' self-regulated learning (SRL) via prompts and feedback to promote learners' monitoring and regulation of their cognitive, affective, metacognitive and motivational processes to achieve their (sub)goals. This study examines PAs' effectiveness in…
Descriptors: Intelligent Tutoring Systems, Scaffolding (Teaching Technique), Independent Study, Prompting
Yizhou Fan; Luzhen Tang; Huixiao Le; Kejie Shen; Shufang Tan; Yueying Zhao; Yuan Shen; Xinyu Li; Dragan Gaševic – British Journal of Educational Technology, 2025
With the continuous development of technological and educational innovation, learners nowadays can obtain a variety of supports from agents such as teachers, peers, education technologies, and recently, generative artificial intelligence such as ChatGPT. In particular, there has been a surge of academic interest in human-AI collaboration and…
Descriptors: College Students, Writing Achievement, Writing Exercises, Artificial Intelligence
Nelekar, Shreeya; Abdulrahman, Amal; Gupta, Manik; Richards, Deborah – British Journal of Educational Technology, 2022
Stress has become one of the major reasons for many mental health related issues among students of all age groups, which has resulted in devastating personal losses including suicide. Societal and familial pressure to succeed is high, particularly in developing countries where education is highly valued as a key enabler. As part of stress…
Descriptors: Intelligent Tutoring Systems, Anxiety, Foreign Countries, College Students
John Sabatini; Arthur C. Graesser; John Hollander; Tenaha O'Reilly – British Journal of Educational Technology, 2023
We argue in this paper that there is currently no adequate theoretical framework or model that spans the twelve odd year trajectory from non-reader to proficient reader, nor addresses fine-grain skill acquisition, mastery and integration. The target construct itself, reading proficiency, as often operationalized as an endpoint of formal secondary…
Descriptors: Literacy Education, Scaffolding (Teaching Technique), Decision Making, Artificial Intelligence
del Olmo-Muñoz, Javier; González-Calero, José Antonio; Diago, Pascual D.; Arnau, David; Arevalillo-Herráez, Miguel – British Journal of Educational Technology, 2022
Problem solving is often regarded as one of the most essential cognitive functions in our daily lives, and, for that reason, educational theorists have long stressed the need for its development. As cognitive flexibility is a fundamental characteristic necessary throughout the problem-solving process, the purpose of this study is to analyse…
Descriptors: Problem Solving, Arithmetic, Grade 5, Grade 6
Wang, Shanyong; Yu, Haotian; Hu, Xianfeng; Li, Jun – British Journal of Educational Technology, 2020
The advancement of technology, especially the development and application of artificial intelligence, has deeply affected the education sector and brought opportunities for pedagogical adaptation. Intelligent tutoring systems, a major application of artificial intelligence in education, have drawn extensive concerns. However, in reality, the…
Descriptors: College Faculty, Teacher Attitudes, Technology Integration, Intelligent Tutoring Systems
Olsen, Jennifer K.; Sharma, Kshitij; Rummel, Nikol; Aleven, Vincent – British Journal of Educational Technology, 2020
The analysis of multiple data streams is a long-standing practice within educational research. Both multimodal data analysis and temporal analysis have been applied successfully, but in the area of collaborative learning, very few studies have investigated specific advantages of multiple modalities versus a single modality, especially combined…
Descriptors: Cooperative Learning, Learning Analytics, Data Use, Data Collection
du Boulay, Benedict – British Journal of Educational Technology, 2019
Intelligent Tutoring systems (ITSs) and Intelligent Learning Environments (ILEs) have been developed and evaluated over the last 40 years. Recent meta-analyses show that they perform well enough to act as effective classroom assistants under the guidance of a human teacher. Despite this success, they have been criticised as embodying a retrograde…
Descriptors: Intelligent Tutoring Systems, Teaching Methods, Meta Analysis, Artificial Intelligence
Rosé, Carolyn P.; McLaughlin, Elizabeth A.; Liu, Ran; Koedinger, Kenneth R. – British Journal of Educational Technology, 2019
Using data to understand learning and improve education has great promise. However, the promise will not be achieved simply by AI and Machine Learning researchers developing innovative models that more accurately predict labeled data. As AI advances, modeling techniques and the models they produce are getting increasingly complex, often involving…
Descriptors: Discovery Learning, Man Machine Systems, Artificial Intelligence, Models
Bush, Jeffrey B. – British Journal of Educational Technology, 2021
Rational number and fractions concepts are inherently difficult; and lack of mastery often holds students back from success in subsequent mathematics courses. This paper describes design characteristics of a software based, adaptive, rational number tutor with virtual manipulatives, realistic contexts, and procedural feedback. Then, the paper…
Descriptors: Manipulative Materials, Intervention, Concept Formation, Fractions
Standen, Penelope J.; Brown, David J.; Taheri, Mohammad; Galvez Trigo, Maria J.; Boulton, Helen; Burton, Andrew; Hallewell, Madeline J.; Lathe, James G.; Shopland, Nicholas; Blanco Gonzalez, Maria A.; Kwiatkowska, Gosia M.; Milli, Elena; Cobello, Stefano; Mazzucato, Annaleda; Traversi, Marco; Hortal, Enrique – British Journal of Educational Technology, 2020
Artificial intelligence tools for education (AIEd) have been used to automate the provision of learning support to mainstream learners. One of the most innovative approaches in this field is the use of data and machine learning for the detection of a student's affective state, to move them out of negative states that inhibit learning, into…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Identification
Xu, Zhihong; Wijekumar, Kausalai; Ramirez, Gilbert; Hu, Xueyan; Irey, Robin – British Journal of Educational Technology, 2019
This meta-analysis examined the effectiveness of improving reading comprehension for students in K-12 classrooms using intelligent tutoring systems (ITSs), a computer-based learning environment that provides customizable and immediate feedback to the learner. Nineteen studies from 13 publications incorporating approximately 10 000 students were…
Descriptors: Reading Comprehension, Meta Analysis, Intelligent Tutoring Systems, Effect Size
Qin, Fen; Li, Kai; Yan, Jianyuan – British Journal of Educational Technology, 2020
Artificial Intelligence (AI) has penetrated the field of education. Trust has long been regarded as a driver for the acceptance of technology. Netnography and interviews were used to investigate trust in AI-based educational systems from the perspective of users. We identified the factors influencing trust in AI-based educational systems and…
Descriptors: Trust (Psychology), Artificial Intelligence, Classification, Context Effect
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