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Stockinger, Kristina; Dresel, Markus; Dickhäuser, Oliver; Daumiller, Martin – Educational Psychology, 2021
University instructors' goals for teaching are important for teaching quality. However, studies examining factors that shape instructors' goal adoption are lacking. Using data from 785 instructors, we investigated whether implicit theories (ITs) about the malleability of intelligence constitute one such factor. Following achievement goal theory…
Descriptors: College Faculty, Teacher Attitudes, Intelligence, Learning Theories
Humes, Larry E. – Journal of Speech, Language, and Hearing Research, 2021
Purpose: This article aimed to document longitudinal changes in auditory function, including measures of temporal processing, and to examine the associations between observed changes in auditory and cognitive function in middle-aged and older adults. Method: This was a prospective longitudinal study of 98 adults (66 women) with baseline ages…
Descriptors: Hearing Impairments, Intelligence Tests, Older Adults, Auditory Perception
Ko, Chia-Yin; Leu, Fang-Yie – IEEE Transactions on Education, 2021
Contribution: This study applies supervised and unsupervised machine learning (ML) techniques to discover which significant attributes that a successful learner often demonstrated in a computer course. Background: Students often experienced difficulties in learning an introduction to computers course. This research attempts to investigate how…
Descriptors: Undergraduate Students, Student Characteristics, Academic Achievement, Predictor Variables
Kelly, M. P.; Reed, P. – Focus on Autism and Other Developmental Disabilities, 2021
"Stimulus over-selectivity" describes a phenomenon in which an individual responds only to a subset of the stimuli present in the environment and, thus, may restrict learning. This study aimed to develop understanding of the nature and role of over-selectivity in autism spectrum disorder (ASD) by analyzing the relationship of…
Descriptors: Autism, Pervasive Developmental Disorders, Behavior Problems, Cognitive Processes
Vanichvasin, Patchara – International Education Studies, 2021
The research aimed to: 1) develop the chatbot; 2) evaluate its effectiveness; and 3) investigate its effects on students' research knowledge. The sample consisted of 36 Thai university students. The research instruments consisted of: 1) the chatbot; 2) an evaluation form; 3) an effectiveness questionnaire; and 4) research tests. Data analysis used…
Descriptors: Educational Technology, Computer Mediated Communication, Instructional Effectiveness, Research Skills
Syaiful; Kamid; Huda, Nizlel – International Journal of Evaluation and Research in Education, 2021
This study aimed to determine the emotional intelligence of junior high school students, especially in managing emotions, recognizing emotions, and motivating themselves. This was quantitative study with survey design. There were 102 respondents participated in this research that were obtained based on purposive technique. The instruments used in…
Descriptors: Emotional Intelligence, Junior High School Students, Mathematics Education, Emotional Response
Pham, Kien Thi – Journal of Social Studies Education Research, 2021
The purpose of the article is to assert Marx's correctness in maintaining the role of the productive forces in the production process. The paper clarifies the concept of productive forces, describes the factors that make up productive forces, and looks at productive forces in social development. Nowadays, in the Fourth Industrial Revolution,…
Descriptors: Industrialization, Labor Force, History, Political Attitudes
Huang, Carolin; Samek, Toni; Shiri, Ali – Journal of Education for Library and Information Science, 2021
The growth of artificial intelligence (AI) technologies has affected higher education in a dramatic way, shifting the norms of teaching and learning. With these shifts come major ethical questions relating to surveillance, exacerbated social inequality, and threats to job security. This article overviews some of the discourses that are developing…
Descriptors: Artificial Intelligence, Ethics, Educational Technology, Higher Education
Lazzaro, Giulia; Costanzo, Floriana; Varuzza, Cristiana; Rossi, Serena; De Matteis, Maria Elena; Vicari, Stefano; Menghini, Deny – Scientific Studies of Reading, 2021
Emerging evidence suggests that the combination of transcranial direct current stimulation (tDCS) and reading training may provide promising benefits for dyslexia; however, the clinical effects and the role of individual differences in tDCS outcomes for dyslexia remain unclear. To this end, the present study investigated the effects of tDCS on…
Descriptors: Dyslexia, Reading Instruction, Teaching Methods, Stimuli
Eser, Mehmet Taha; Çobanoglu Aktan, Derya – International Journal of Curriculum and Instruction, 2021
By applying educational data mining methods to big data related to large-scale exams, functional relationships are discovered in a basic sense and hidden pattern(s) can be revealed. Within the scope of the research, to show how the self-organizing map (SOM) method can be used in terms of educational data mining, how SOM differs from other…
Descriptors: Science Instruction, Scientific Literacy, Data Analysis, Artificial Intelligence
Treleaven, Shanley B.; Coalson, Geoffrey A. – Journal of Speech, Language, and Hearing Research, 2021
Purpose: Adults who stutter (AWS) often attempt, with varying degrees of success, to suppress their stuttered speech. The ability to effectively suppress motoric behavior after initiation relies on executive functions such as nonselective inhibition. Although previous studies found that AWS were slower to inhibit manual, button-press response than…
Descriptors: Verbal Ability, Verbal Communication, Responses, Inhibition
Lorenzo, Neus; Gallon, Ray; Palau, Ramon; Mogas, Jordi – Technology, Knowledge and Learning, 2021
This paper provides theoretical reflections and recommendations for implementing smart learning spaces in schools. Learning resource networks are enlarging students' opportunities for exploring alternative formal, non-formal and informal education, in physical and virtual learning spaces, inside and outside traditional classrooms. Smart Pedagogy…
Descriptors: Educational Technology, Artificial Intelligence, Electronic Learning, Program Implementation
Albreiki, Balqis; Zaki, Nazar; Alashwal, Hany – Education Sciences, 2021
Educational Data Mining plays a critical role in advancing the learning environment by contributing state-of-the-art methods, techniques, and applications. The recent development provides valuable tools for understanding the student learning environment by exploring and utilizing educational data using machine learning and data mining techniques.…
Descriptors: Literature Reviews, Grade Prediction, Artificial Intelligence, Educational Environment
Lee, Alwyn Vwen Yen – Educational Technology & Society, 2021
The understanding of online classroom talk is a challenge even with current technological advancements. To determine the quality of ideas in classroom talk for individual and groups of students, a new approach such as precision education will be needed to integrate learning analytics and machine learning techniques to improve the quality of…
Descriptors: Learning Analytics, Artificial Intelligence, Classroom Communication, Electronic Learning
Kahn, Ken; Winters, Niall – British Journal of Educational Technology, 2021
Constructionism, long before it had a name, was intimately tied to the field of Artificial Intelligence. Soon after the birth of Logo at BBN, Seymour Papert set up the Logo Group as part of the MIT AI Lab. Logo was based upon Lisp, the first prominent AI programming language. Many early Logo activities involved natural language processing,…
Descriptors: Artificial Intelligence, Man Machine Systems, Programming Languages, Programming

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