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Charlotte N. Gunawardena; Yan Chen; Nick Flor; Damien Sánchez – Online Learning, 2023
Gunawardena et al.'s (1997) Interaction Analysis Model (IAM) is one of the most frequently employed frameworks to guide the qualitative analysis of social construction of knowledge online. However, qualitative analysis is time consuming, and precludes immediate feedback to revise online courses while being delivered. To expedite analysis with a…
Descriptors: Models, Learning Processes, Knowledge Level, Online Courses
Koole, Marguerite – International Journal of Mobile and Blended Learning, 2018
This article is primarily a theoretical piece that uses a model of mobile learning, the FRAME model (Koole 2009), to explore a mobile teacher-training project that took place in Papua New Guinea: the SMS Story. The author takes a sociomaterial perspective, drawing upon Barad's agential realism and Sørensen's multiplicity perspective. As the author…
Descriptors: Electronic Learning, Teacher Education, Foreign Countries, Models
Haymes, Tom – Current Issues in Education, 2020
Productive "Third Spaces" are often an afterthought when designing learning environments, both in a physical sense and online. These areas, properly mediated by technology and designed around humans, can often be a key facilitator for student success. The STAC Model is designed to provide a framework for understanding what makes these…
Descriptors: Models, Informal Education, Instructional Design, Technology Uses in Education
Rus, Vasile; Gautam, Dipesh; Swiecki, Zachari; Shaffer, David W.; Graesser, Arthur C. – International Educational Data Mining Society, 2016
Engineering virtual internships are simulations where students role play as interns at fictional companies, working to create engineering designs. To improve the scalability of these virtual internships, a reliable automated assessment system for tasks submitted by students is necessary. Therefore, we propose a machine learning approach to…
Descriptors: Engineering Education, Internship Programs, Computer Simulation, Models
Lagus, Jarkko; Longi, Krista; Klami, Arto; Hellas, Arto – ACM Transactions on Computing Education, 2018
The computing education research literature contains a wide variety of methods that can be used to identify students who are either at risk of failing their studies or who could benefit from additional challenges. Many of these are based on machine-learning models that learn to make predictions based on previously observed data. However, in…
Descriptors: Computer Science Education, Transfer of Training, Programming, Educational Objectives
Baker, Ryan S. – International Journal of Artificial Intelligence in Education, 2016
The initial vision for intelligent tutoring systems involved powerful, multi-faceted systems that would leverage rich models of students and pedagogies to create complex learning interactions. But the intelligent tutoring systems used at scale today are much simpler. In this article, I present hypotheses on the factors underlying this development,…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Hypothesis Testing, Data Collection
Bull, Susan; Kay, Judy – International Journal of Artificial Intelligence in Education, 2016
The SMILI? (Student Models that Invite the Learner In) Open Learner Model Framework was created to provide a coherent picture of the many and diverse forms of Open Learner Models (OLMs). The aim was for SMILI? to provide researchers with a systematic way to describe, compare and critique OLMs. We expected it to highlight those areas where there…
Descriptors: Educational Research, Data Collection, Data Analysis, Intelligent Tutoring Systems
Ellis, R. A.; Goodyear, P. – Review of Education, 2016
Learning space research is a relatively new field of study that seeks to inform the design, evaluation and management of learning spaces. This paper reviews a dispersed and fragmented literature relevant to understanding connections between university learning spaces and student learning activities. From this review, the paper distils a number of…
Descriptors: Educational Environment, Educational Research, Higher Education, Universities
Janicki, Thomas N.; Cummings, Jeffrey; Healy, R. Joseph – Information Systems Education Journal, 2015
Individuals have increasing options on retrieving information related to hardware and software. Specific hardware devices include desktops, tablets and smart devices. Also, the number of software applications has significantly increased the user's capability to access data. Software applications include the traditional web site, smart device…
Descriptors: Computer Science Education, Man Machine Systems, Computer Software, Curriculum Development
Prestopnik, Nathan R. – ProQuest LLC, 2013
Humanity has entered an era where computing technology is virtually ubiquitous. From websites and mobile devices to computers embedded in appliances on our kitchen counters and automobiles parked in our driveways, information and communication technologies (ICTs) and IT artifacts are fundamentally changing the ways we interact with our world.…
Descriptors: Information Technology, Man Machine Systems, Design, Models
Selmeczy, Diana; Dobbins, Ian G. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2014
The Remember/Know procedure, developed by Tulving (1985) to capture the distinction between the conscious correlates of episodic and semantic retrieval, has spawned considerable research and debate. However, only a handful of reports have examined the recognition content beyond this dichotomous simplification. To address this, we collected…
Descriptors: Memory, Recognition (Psychology), Semantics, Word Frequency
Dillenbourg, Pierre – International Journal of Artificial Intelligence in Education, 2016
How does AI&EdAIED today compare to 25 years ago? This paper addresses this evolution by identifying six trends. The trends are ongoing and will influence learning technologies going forward. First, the physicality of interactions and the physical space of the learner became genuine components of digital education. The frontier between the…
Descriptors: Artificial Intelligence, Educational Trends, Trend Analysis, Educational Technology
Seedhouse, Paul; Knight, Dawn – Applied Linguistics, 2016
There is currently an explosion in the number and range of new devices coming onto the technology market that use digital sensor technology to track aspects of human behaviour. In this article, we present and exemplify a three-stage model for the application of digital sensor technology in applied linguistics that we have developed, namely,…
Descriptors: Foreign Countries, Applied Linguistics, Man Machine Systems, Measurement Equipment
Carle, Andrew Jacob – ProQuest LLC, 2012
I begin by introducing Virtual Design Apprenticeship (VDA), a learning model--built on a solid foundation of education principles and theories--that promotes learning of design skills via overlay design tools. In VDA, when an individual needs to learn a new design skill or paradigm she is provided accessible, concrete examples that have been…
Descriptors: Instructional Design, Visual Aids, Models, Novices
Evanini, Keelan; Heilman, Michael; Wang, Xinhao; Blanchard, Daniel – ETS Research Report Series, 2015
This report describes the initial automated scoring results that were obtained using the constructed responses from the Writing and Speaking sections of the pilot forms of the "TOEFL Junior"® Comprehensive test administered in late 2011. For all of the items except one (the edit item in the Writing section), existing automated scoring…
Descriptors: Computer Assisted Testing, Automation, Language Tests, Second Language Learning