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Tsabari, Stav; Segal, Avi; Gal, Kobi – International Educational Data Mining Society, 2023
Automatically identifying struggling students learning to program can assist teachers in providing timely and focused help. This work presents a new deep-learning language model for predicting "bug-fix-time", the expected duration between when a software bug occurs and the time it will be fixed by the student. Such information can guide…
Descriptors: College Students, Computer Science Education, Programming, Error Patterns
Saucerman, Jenny; Ruis, A. R.; Shaffer, David Williamson – Journal of Learning Analytics, 2017
Learning to solve "complex problems"--problems whose solutions require the application of more than basic facts and skills--is critical to meaningful participation in the economic, social, and cultural life of the digital age. In this paper, we use a theoretical understanding of how professionals use reflection-in-action to solve complex…
Descriptors: Reflection, Problem Solving, Automation, Skill Development
Conway, Laura J.; Levickis, Penny A.; Smith, Jodie; Mensah, Fiona; Wake, Melissa; Reilly, Sheena – International Journal of Language & Communication Disorders, 2018
Background: Identifying risk and protective factors for language development informs interventions for children with developmental language disorder (DLD). Maternal responsive and intrusive communicative behaviours are associated with language development. Mother-child interaction quality may influence how children use these behaviours in language…
Descriptors: Mothers, Parent Child Relationship, Video Technology, Play
Andrade, Alejandro; Delandshere, Ginette; Danish, Joshua A. – Journal of Learning Analytics, 2016
One of the challenges many learning scientists face is the laborious task of coding large amounts of video data and consistently identifying social actions, which is time consuming and difficult to accomplish in a systematic and consistent manner. It is easier to catalog observable behaviours (e.g., body motions or gaze) without explicitly…
Descriptors: Student Behavior, Data Analysis, Models, Video Technology
Adu-Gyamfi, Kwaku; Stiff, Lee V.; Bosse, Michael J. – School Science and Mathematics, 2012
Translation errors and conceptual misunderstandings made by students translating among graphical, tabular, and symbolic representations of linear functions were examined. The study situated student errors in the context of the "Translation-Verification Model" developed specifically for the purpose of explaining student behavior during the process…
Descriptors: Student Behavior, Translation, Error Patterns, Models
Reese, Elaine; Haden, Catherine A.; Baker-Ward, Lynne; Bauer, Patricia; Fivush, Robyn; Ornstein, Peter A. – Journal of Cognition and Development, 2011
Personal narratives are integral to autobiographical memory and to identity, with coherent personal narratives being linked to positive developmental outcomes across the lifespan. In this article, we review the theoretical and empirical literature that sets the stage for a new lifespan model of personal narrative coherence. This new model…
Descriptors: Rhetoric, Laboratories, Personal Narratives, Memory
Scherf, K. Suzanne; Behrmann, Marlene; Kimchi, Ruth; Luna, Beatriz – Child Development, 2009
The developmental trajectory of perceptual organization in humans is unclear. This study investigated perceptual grouping abilities across a wide age range (8-30 years) using a classic compound letter global/local (GL) task and a more fine-grained microgenetic prime paradigm (MPP) with both few- and many-element hierarchical displays. In the GL…
Descriptors: Visual Perception, Adolescents, Young Adults, Age Groups
Davis, Colin J. – Psychological Review, 2010
Visual word identification requires readers to code the identity and order of the letters in a word and match this code against previously learned codes. Current models of this lexical matching process posit context-specific letter codes in which letter representations are tied to either specific serial positions or specific local contexts (e.g.,…
Descriptors: Identification, Word Recognition, Models, Coding

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