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Douglas J. Fiore – Routledge, Taylor & Francis Group, 2025
Accessible and practical, the sixth edition of "School-Community Relations" provides aspiring educational leaders with the skills to establish strong systems for communicating with their various school constituencies and to improve public relations at all levels. This textbook uses real-life examples to illustrate the ways in which…
Descriptors: School Community Relationship, Partnerships in Education, Teacher Participation, Student Participation
Thada Jantakoon; Thiti Jantakun; Kitsadaporn Jantakun; Weerapa Pongpanich; Rungfa Pasmala; Panita Wannapiroon; Prachyanun Nilsook – Contemporary Educational Technology, 2025
The increasing integration of artificial intelligence (AI) in education has raised significant questions about its pedagogical value, especially in language learning. This meta-analysis examines the extent to which AI contributes to the development of English-speaking and listening skills. A systematic review of the literature was conducted by the…
Descriptors: Literature Reviews, Meta Analysis, Artificial Intelligence, Listening Skills
Qian Chen – International Journal of Information and Communication Technology Education, 2025
With the continuous progress of educational technology, personalized teaching has become a key way to improve teaching quality. In view of the current situation that English teaching content lacks personalization and interactivity, this paper proposes a personalized English teaching content generation system based on neural network (NN). The…
Descriptors: Electronic Learning, Individualized Instruction, Artificial Intelligence, Learner Engagement
Minkai Wang; Jingdong Zhu; Gwo-Jen Hwang; Shao-Chen Chang; Qi-Fan Yang; Di Zhang – Journal of Computer Assisted Learning, 2025
Background: STEM education aims to develop innovation and problem-solving skills through interdisciplinary learning, yet struggles to foster student engagement and interdisciplinary thinking. Whilst alternate reality games (ARGs) can boost motivation via game-based problem-solving, integrating large language models (LLMs) remains underexplored.…
Descriptors: Learner Engagement, STEM Education, Natural Language Processing, Artificial Intelligence
Hsu, Hao-Hsuan; Huang, Nen-Fu – IEEE Transactions on Learning Technologies, 2022
This article introduces Xiao-Shih, the first intelligent question answering bot on Chinese-based massive open online courses (MOOCs). Question answering is critical for solving individual problems. However, instructors on MOOCs must respond to many questions, and learners must wait a long time for answers. To address this issue, Xiao-Shih…
Descriptors: Foreign Countries, Artificial Intelligence, Online Courses, Natural Language Processing
Girouard-Hallam, Lauren N.; Danovitch, Judith H. – Developmental Psychology, 2022
As children increasingly interact with digital voice assistants, it is important to know whether they treat these devices as reliable information sources. Two studies investigated children's trust in and recall of statements made by a novel voice assistant and a human informant. In Study 1, children ages 4-5 (M[subscript age] = 5.05; 20 boys, 20…
Descriptors: Artificial Intelligence, Assistive Technology, Trust (Psychology), Preschool Children
Thongprasit, Junjiraporn; Wannapiroon, Panita – International Education Studies, 2022
Nowadays, Information Technology is an integrated as a part of our life activities. It does not affect only teaching and learning methods at all levels, but also the teaching styles of each teacher with suitable for the digital age. Therefore, the standardized platform should create for all teachers to effectively serve the future education…
Descriptors: Educational Technology, Technology Uses in Education, Artificial Intelligence, Integrated Learning Systems
Susnjak, Teo; Ramaswami, Gomathy Suganya; Mathrani, Anuradha – International Journal of Educational Technology in Higher Education, 2022
This study investigates current approaches to learning analytics (LA) dashboarding while highlighting challenges faced by education providers in their operationalization. We analyze recent dashboards for their ability to provide actionable insights which promote informed responses by learners in making adjustments to their learning habits. Our…
Descriptors: Learning Analytics, Computer Interfaces, Artificial Intelligence, Prediction
Radosavljevic, Vitomir; Radosavljevic, Slavica; Jelic, Gordana – Interactive Learning Environments, 2022
This paper introduces the smart classroom learning model based on the concept of ambient intelligence. By analyzing a smart classroom, the ambient intelligence system detects a student and determines their level of fatigue based on the data about their previous daily academic activities. This information is then used to assign the student the…
Descriptors: Virtual Classrooms, Educational Technology, Technology Uses in Education, Artificial Intelligence
Ishihara, Makio; Rattanachinalai, Pongpun – Education and Information Technologies, 2022
This paper designs and develops a computer programming learning system for total beginners and those who have no programming experience. The traditional computer programming learning systems require prior knowledge about variables, their types, operators for arithmetic calculations and relational calculations etc., for adopting a wide range of…
Descriptors: Computer Science Education, Programming, Novices, Task Analysis
Li, Yuheng; Rakovic, Mladen; Poh, Boon Xin; Gaševic, Dragan; Chen, Guanliang – International Educational Data Mining Society, 2022
Learning objectives, especially those well defined by applying Bloom's taxonomy for Cognitive Objectives, have been widely recognized as important in various teaching and learning practices. However, many educators have difficulties developing learning objectives appropriate to the levels in Bloom's taxonomy, as they need to consider the…
Descriptors: Educational Objectives, Taxonomy, Universities, Cognitive Ability
Oxendine, Symphony D.; Robinson, Kerry K.; Parker, Michele A. – To Improve the Academy, 2022
This article outlines an appreciative inquiry (AI) into a departmental professional development process and describes the resulting implementation of an appreciative peer evaluation meeting as one part of the new professional development process. Using AI, a departmental faculty development committee sought to re-envision the professional…
Descriptors: Departments, Faculty Development, Teacher Evaluation, Peer Evaluation
Ben Soussia, Amal; Labba, Chahrazed; Roussanaly, Azim; Boyer, Anne – International Journal of Information and Learning Technology, 2022
Purpose: The goal is to assess performance prediction systems (PPS) that are used to assist at-risk learners. Design/methodology/approach: The authors propose time-dependent metrics including earliness and stability. The authors investigate the relationships between the various temporal metrics and the precision metrics in order to identify the…
Descriptors: Performance, Prediction, Student Evaluation, At Risk Students
Chanaa, Abdessamad; El Faddouli, Nour-eddine – International Journal of Information and Communication Technology Education, 2022
Massive open online courses (MOOCs) have evolved rapidly in recent years due to their open and massive nature. However, MOOCs suffer from a high dropout rate, since learners struggle to stay cognitively and emotionally engaged. Learner feedback is an excellent way to understand learner behaviour and model early decision making. In the presented…
Descriptors: MOOCs, Student Attitudes, Data Analysis, Electronic Learning
Mead, Alan D.; Zhou, Chenxuan – Journal of Applied Testing Technology, 2022
This study fit a Naïve Bayesian classifier to the words of exam items to predict the Bloom's taxonomy level of the items. We addressed five research questions, showing that reasonably good prediction of Bloom's level was possible, but accuracy varies across levels. In our study, performance for Level 2 was poor (Level 2 items were misclassified…
Descriptors: Artificial Intelligence, Prediction, Taxonomy, Natural Language Processing

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