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Shen, Guohua; Yang, Sien; Huang, Zhiqiu; Yu, Yaoshen; Li, Xin – Education and Information Technologies, 2023
Due to the growing demand for information technology skills, programming education has received increasing attention. Predicting students' programming performance helps teachers realize their teaching effect and students' learning status in time to provide support for students. However, few of the existing researches have taken the code that…
Descriptors: Prediction, Programming, Student Characteristics, Profiles
Shan Li; Xiaoshan Huang; Tingting Wang; Juan Zheng; Susanne P. Lajoie – Journal of Computing in Higher Education, 2025
Coding think-aloud transcripts is time-consuming and labor-intensive. In this study, we examined the feasibility of predicting students' reasoning activities based on their think-aloud transcripts by leveraging the affordances of text mining and machine learning techniques. We collected the think-aloud data of 34 medical students as they diagnosed…
Descriptors: Information Retrieval, Artificial Intelligence, Prediction, Abstract Reasoning
Guediche, Sara; Fiez, Julie A. – Journal of Speech, Language, and Hearing Research, 2021
Purpose: Morse code as a form of communication became widely used for telegraphy, radio and maritime communication, and military operations, and remains popular with ham radio operators. Some skilled users of Morse code are able to comprehend a full sentence as they listen to it, while others must first transcribe the sentence into its written…
Descriptors: Coding, Comprehension, Prediction, Recall (Psychology)
Abdullahi Yusuf; Norah Md Noor; Shamsudeen Bello – Education and Information Technologies, 2024
Studies examining students' learning behavior predominantly employed rich video data as their main source of information due to the limited knowledge of computer vision and deep learning algorithms. However, one of the challenges faced during such observation is the strenuous task of coding large amounts of video data through repeated viewings. In…
Descriptors: Learning Analytics, Student Behavior, Video Technology, Classification
Bierema, Andrea; Hoskinson, Anne-Marie; Moscarella, Rosa; Lyford, Alex; Haudek, Kevin; Merrill, John; Urban-Lurain, Mark – International Journal of Research & Method in Education, 2021
As we take advantage of new technologies that allow us to streamline the coding process of large qualitative datasets, we must consider whether human cognitive bias may introduce statistical bias in the process. Our research group analyzes large sets of student responses by developing computer models that are trained using human-coded responses…
Descriptors: Cognitive Processes, Bias, Educational Researchers, Educational Research
Mayer, Christian W. F.; Ludwig, Sabrina; Brandt, Steffen – Journal of Research on Technology in Education, 2023
This study investigates the potential of automated classification using prompt-based learning approaches with transformer models (large language models trained in an unsupervised manner) for a domain-specific classification task. Prompt-based learning with zero or few shots has the potential to (1) make use of artificial intelligence without…
Descriptors: Prompting, Classification, Artificial Intelligence, Natural Language Processing
Janet E. Rosenbaum; Lisa C. Dierker – Journal of Statistics and Data Science Education, 2024
Self-efficacy is associated with a range of educational outcomes, including science and math degree attainment. Project-based statistics courses have the potential to increase students' math self-efficacy because projects may represent a mastery experience, but students enter courses with preexisting math self-efficacy. This study explored…
Descriptors: Self Efficacy, Statistics Education, Introductory Courses, Self Esteem
Introducing High School Statistics Teachers to Predictive Modelling and APIs Using Code-Driven Tools
Fergusson, Anna; Pfannkuch, Maxine – Statistics Education Research Journal, 2022
Tasks for teaching predictive modelling and APIs often require learners to use code-driven tools. Minimal research, however, exists about the design of tasks that support the introduction of high school students and teachers to these new statistical and computational methods. Using a design-based research approach, a web-based task was developed.…
Descriptors: High School Teachers, Statistics Education, Prediction, Mathematical Models
Agres, Kat; Abdallah, Samer; Pearce, Marcus – Cognitive Science, 2018
A basic function of cognition is to detect regularities in sensory input to facilitate the prediction and recognition of future events. It has been proposed that these implicit expectations arise from an internal predictive coding model, based on knowledge acquired through processes such as statistical learning, but it is unclear how different…
Descriptors: Auditory Stimuli, Cognitive Processes, Coding, Memory
Van Dessel, Pieter; Eder, Andreas B.; Hughes, Sean – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2018
Over the past decade an increasing number of studies across a range of domains have shown that the repeated performance of approach and avoidance (AA) actions in response to a stimulus leads to changes in the evaluation of that stimulus. The dominant (motivational-systems) account in this area claims that these effects are caused by a rewiring of…
Descriptors: Social Psychology, Motivation, Behavior, Training
van Schalkwyk, Gerrit I.; Volkmar, Fred R.; Corlett, Philip R. – Journal of Autism and Developmental Disorders, 2017
The co-occurrence of psychotic and autism spectrum disorder (ASD) symptoms represents an important clinical challenge. Here we consider this problem in the context of a computational psychiatry approach that has been applied to both conditions--predictive coding. Some symptoms of schizophrenia have been explained in terms of a failure of top-down…
Descriptors: Autism, Pervasive Developmental Disorders, Symptoms (Individual Disorders), Coding
Venkadasalam, Vaunam P.; Ganea, Patricia A. – Journal of Cognition and Development, 2018
This study examined whether children 4- and 5-years-old (N = 156) can revise a physical science misconception from different types of picture books. A realistic fiction book and informational book with identical images matched in word count and reading difficulty level were compared to a control book about plants. In the pretest and posttest,…
Descriptors: Young Children, Misconceptions, Scientific Concepts, Comparative Analysis
Monaghan, Padraic; Rowland, Caroline F. – Language Learning, 2017
Historically, first language acquisition research was a painstaking process of observation, requiring the laborious hand coding of children's linguistic productions, followed by the generation of abstract theoretical proposals for how the developmental process unfolds. Recently, the ability to collect large-scale corpora of children's language…
Descriptors: Computational Linguistics, Language Acquisition, Language Research, Second Language Learning
Nuske, Heather Joy; Hedley, Darren; Tseng, Chen Hsiang; Begeer, Sander; Dissanayake, Cheryl – Journal of Autism and Developmental Disorders, 2018
Children with autism experience challenges with emotion regulation. It is unclear how children's management of their emotions is associated with their family's quality of life. Forty-three preschoolers with autism and 28 typically developing preschoolers were coded on emotion regulation strategies used during low-level stress tasks. Parents…
Descriptors: Self Control, Preschool Children, Quality of Life, Autism
Polinsky, Naomi; Perez, Jasmin; Grehl, Mora; McCrink, Koleen – Mind, Brain, and Education, 2017
Longitudinal spatial language intervention studies have shown that greater exposure to spatial language improves children's performance on spatial tasks. Can short naturalistic, spatial language interactions also evoke improved spatial performance? In this study, parents were asked to interact with their child at a block wall exhibit in a…
Descriptors: Museums, Teaching Methods, Spatial Ability, Parent Child Relationship