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Xiaona Xia – Interactive Learning Environments, 2023
Effective analysis and demonstration of these data features is of great significance for the optimization of interactive learning environment and learning behavior. Therefore, we take the big data set of learning behavior generated by an online interactive learning environment as the research object, define the features of learning behavior, and…
Descriptors: Learning Strategies, Interaction, Educational Environment, Learning Analytics
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Paras Sharma; Angela E. B. Stewart; Qichang Li; Krit Ravichander; Erin Walker – International Educational Data Mining Society, 2024
Open-ended learning environments (OELEs) involve high learner agency in defining learning goals and multiple pathways to achieve those goals. These tasks involve learners transitioning through self-regulated learning (SRL) phases by actively setting goals, applying different strategies for those goals, and monitoring performance to update their…
Descriptors: Self Management, Learning Strategies, Learning Activities, Models
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Zhang, Ningyu; Biswas, Gautam; Hutchins, Nicole – International Journal of Artificial Intelligence in Education, 2022
Strategies are an important component of self-regulated learning frameworks. However, the characterization of strategies in these frameworks is often incomplete: (1) they lack an operational definition of strategies; (2) there is limited understanding of how students develop and apply strategies; and (3) there is a dearth of systematic and…
Descriptors: Learning Strategies, Student Behavior, Educational Environment, Grade 6
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Hutt, Stephen; Ocumpaugh, Jaclyn; Ma, Juliana; Andres, Alexandra L.; Bosch, Nigel; Paquette, Luc; Biswas, Gautam; Baker, Ryan S. – International Educational Data Mining Society, 2021
Self-regulated learning (SRL) is a critical 21st -century skill. In this paper, we examine SRL through the lens of the searching, monitoring, assessing, rehearsing, and translating (SMART) schema for learning operations. We use microanalysis to measure SRL behaviors as students interact with a computer-based learning environment, Betty's Brain. We…
Descriptors: Models, Self Control, Learning Strategies, Student Behavior
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Kember, David; Webster, Beverley J.; Chan, Wincy S. C. – Educational Psychology, 2020
The 3P (presage, process, product) model was introduced as a conceptualisation to underpin research into students' approaches to learning (SAL). This paper proposes the refocusing of the 3P model by formulating the initial presage phase as a teaching and learning environment, thus making the 3P model more consistent with SAL research which…
Descriptors: Models, Educational Environment, College Students, Foreign Countries
Wenmoth, Derek; Jones, Marsha; DiMartino, Joseph – Aurora Institute, 2021
The global COVID-19 pandemic pulled back the curtain on the growing need for greater student agency and student engagement. As we rethink the future of education in a post-pandemic world, learner agency must be at the center of learning designs and learning models so that we can support students anytime, anyplace, and at any pace. We must…
Descriptors: Learner Engagement, Personal Autonomy, Models, Student Empowerment
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Thapliyal, Monika; Ahuja, Neelu Jyothi; Shankar, Achyut; Cheng, Xiaochun; Kumar, Manoj – Journal of Computing in Higher Education, 2022
This paper presents the ontological design and implementation of the differentiated learning environment in the domain model of an intelligent tutoring system for children with specific learning disabilities. It addresses the learners need for differentiated instruction in a preferential learning environment. The proposed model helps to identify…
Descriptors: Individualized Instruction, Intelligent Tutoring Systems, Students with Disabilities, Learning Disabilities
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Peterson, Lana; Scharber, Cassandra – Journal of Digital Learning in Teacher Education, 2018
Makerspaces are the latest educational movement that may disrupt the "grammar of schooling." Makerspaces may change the ways schools use technology; change the ways schools engage in learning and teaching; and change the forms of learning that count in schools. However, without deliberate professional learning and planning, the glamor of…
Descriptors: Faculty Development, Training Methods, Elementary Secondary Education, Teaching Models
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Finch, W. Holmes; Cassady, Jerrell C.; Jones, James A. – Journal of Psychoeducational Assessment, 2016
The Learning and Study Strategies Inventory (LASSI) is a very popular tool for measuring the learning and study strategies of high school and college students. Prior research with the LASSI has supported the originally proposed model with three latent traits, with minor variations among the contributing subtests contributing to those traits.…
Descriptors: Learning Strategies, Measures (Individuals), Factor Analysis, Scores
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Adams, Curt M.; Forsyth, Patrick B.; Dollarhide, Ellen; Miskell, Ryan; Ware, Jordan – Teachers College Record, 2015
Background/Context: Schools have differential effects on student learning and development, but research has not generated much explanatory evidence of the social-psychological pathway to better achievement outcomes. Explanatory evidence of how normative conditions enable students to thrive is particularly relevant in the urban context where…
Descriptors: Academic Achievement, Mathematics Achievement, Self Control, Teacher Surveys
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Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – Grantee Submission, 2015
Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…
Descriptors: Educational Environment, Predictive Measurement, Predictor Variables, Cooperative Learning
Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – International Educational Data Mining Society, 2015
Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…
Descriptors: Educational Environment, Predictive Measurement, Predictor Variables, Cooperative Learning
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Ola, Ade G.; Bai, Xue; Omojokun, Emmanuel E. – Research in Higher Education Journal, 2014
Over the years, companies have relied on On-Line Analytical Processing (OLAP) to answer complex questions relating to issues in business environments such as identifying profitability, trends, correlations, and patterns. This paper addresses the application of OLAP in education and learning. The objective of the research presented in the paper is…
Descriptors: Profiles, Database Management Systems, Information Management, Progress Monitoring
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Martin, Justine – Communications in Information Literacy, 2013
Models play an important role in helping practitioners implement and promote information literacy. Over time models can lose relevance with the advances in technology, society, and learning theory. Practitioners and scholars often call for adaptations or transformations of these frameworks to articulate the learning needs in information literacy…
Descriptors: Foreign Countries, Information Literacy, Models, Content Analysis
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Dixon, L. Quentin; Wu, Shuang – Malaysian Journal of Learning and Instruction, 2014
Purpose: This paper examined the application of the input-interaction-output model in English-as-Foreign-Language (EFL) learning environments with four specific questions: (1) How do the three components function in the model? (2) Does interaction in the foreign language classroom seem to be effective for foreign language acquisition? (3) What…
Descriptors: Educational Environment, Models, Interaction, English (Second Language)
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