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Sharma, Priynka; Harkishan, Mayuri – Education and Information Technologies, 2022
Intelligent Tutoring Systems (ITSs) are educational systems that reflect knowledge using artificial intelligence implements. In this paper, we give an outline of the Programming-Tutor architectural design with the core implements on user interaction. This pilot proposal is for designing a model domain of a subset in the computer programming…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Programming, Online Courses
Elvina, Elvina; Karnalim, Oscar; Ayub, Mewati; Wijanto, Maresha Caroline – Journal of Technology and Science Education, 2018
Numerous Program Visualization tools (PVs) have been developed for assisting novice students to understand their source code further. However, none of them are practical to be used in the context of completing programming laboratory task; students are required to keep switching between PV and programming workspace since PV's features are…
Descriptors: Visualization, Programming, Computer Science Education, Intelligent Tutoring Systems
Nongkhai, Lalita Na; Wang, Jingyun; Mendori, Takahiko – International Association for Development of the Information Society, 2022
This paper proposes the design of an ontology of multiple programming languages and give three examples to show the methodology. Our ontology aims to summarize the core of computational thinking logic by elaborating the concepts of three object-oriented programming languages in the industry: Python, Java, and C#. Therefore, the construction of the…
Descriptors: Programming Languages, Computer Science Education, Intelligent Tutoring Systems, Thinking Skills
Cai, Zhiqiang; Hu, Xiangen; Graesser, Arthur C. – Grantee Submission, 2019
Conversational Intelligent Tutoring Systems (ITSs) are expensive to develop. While simple online courseware could be easily authored by teachers, the authoring of conversational ITSs usually involves a team of experts with different expertise, including domain experts, linguists, instruction designers, programmers, artists, computer scientists,…
Descriptors: Programming, Intelligent Tutoring Systems, Courseware, Educational Technology
Rivers, Kelly; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2017
To provide personalized help to students who are working on code-writing problems, we introduce a data-driven tutoring system, ITAP (Intelligent Teaching Assistant for Programming). ITAP uses state abstraction, path construction, and state reification to automatically generate personalized hints for students, even when given states that have not…
Descriptors: Programming, Coding, Computers, Data
Dawar, Deepak – Information Systems Education Journal, 2022
Learning computer programming is a challenging task for most beginners. Demotivation and learned helplessness are pretty common. A novel instructional technique that leverages the value-expectancy motivational model of student learning was conceptualized by the author to counter the lack of motivation in the introductory class. The result was a…
Descriptors: Teaching Methods, Introductory Courses, Computer Science Education, Assignments
Paaßen, Benjamin; Jensen, Joris; Hammer, Barbara – International Educational Data Mining Society, 2016
The first intelligent tutoring systems for computer programming have been proposed more than 30 years ago, mostly focusing on well defined programming tasks e.g. in the context of logic programming. Recent systems also teach complex programs, where explicit modelling of every possible program and mistake is no longer possible. Such systems are…
Descriptors: Intelligent Tutoring Systems, Programming, Computer Science Education, Data
Py, Dominique; Després, Christophe; Jacoboni, Pierre – Technology, Instruction, Cognition and Learning, 2015
Although providing open learner models to teachers and learners has proven effective, building accurate learner models remains a very complex task, partly due to the large amount of data that must be analyzed. We propose a method for specifying an open learner model at the conceptual level. This model re-uses constraints or indicators already…
Descriptors: Open Education, Models, Design, Programming Languages
Olney, Andrew M.; Cade, Whitney L. – Grantee Submission, 2015
This paper proposes a methodology for authoring of intelligent tutoring systems using human computation. The methodology embeds authoring tasks in existing educational tasks to avoid the need for monetary authoring incentives. Because not all educational tasks are equally motivating, there is a tension between designing the human computation task…
Descriptors: Programming, Intelligent Tutoring Systems, Computation, Design
Olsen, Jennifer K.; Belenky, Daniel M.; Aleven, Vincent; Rummel, Nikol; Sewall, Jonathan; Ringenberg, Michael – Grantee Submission, 2014
Authoring tools have been shown to decrease the amount of time and resources needed for the development of Intelligent Tutoring Systems (ITSs). Although collaborative learning has been shown to be beneficial to learning, most of the current authoring tools do not support the development of collaborative ITSs. In this paper, we discuss an extension…
Descriptors: Intelligent Tutoring Systems, Programming, Cooperative Learning, Problem Solving
Olsen, Jennifer K.; Belenky, Daniel M.; Aleven, Vincent; Rummel, Nikol; Sewall, Jonathan; Ringenberg, Michael – Grantee Submission, 2013
Authoring tools for Intelligent Tutoring System (ITS) have been shown to decrease the amount of time that it takes to develop an ITS. However, most of these tools currently do not extend to collaborative ITSs. In this paper, we illustrate an extension to the Cognitive Tutor Authoring Tools (CTAT) to allow for development of collaborative ITSs that…
Descriptors: Intelligent Tutoring Systems, Programming Languages, Fractions, Learning Processes
Le, Nguyen-Thinh; Menzel, Wolfgang – International Journal of Artificial Intelligence in Education, 2009
In this paper, we introduce logic programming as a domain that exhibits some characteristics of being ill-defined. In order to diagnose student errors in such a domain, we need a means to hypothesise the student's intention, that is the strategy underlying her solution. This is achieved by weighting constraints, so that hypotheses about solution…
Descriptors: Intelligent Tutoring Systems, Logical Thinking, Programming, Models
Suraweera, Pramuditha; Mitrovic, Antonija; Martin, Brent – International Journal of Artificial Intelligence in Education, 2010
Intelligent Tutoring Systems (ITS) are effective tools for education. However, developing them is a labour-intensive and time-consuming process. A major share of the effort is devoted to acquiring the domain knowledge that underlies the system's intelligence. The goal of this research is to reduce this knowledge acquisition bottleneck and better…
Descriptors: Intelligent Tutoring Systems, Programming, Engineering, Tutoring
Mavrikis, Manolis; Gutierrez-Santos, Sergio – Computers & Education, 2010
This paper presents a methodology for the design of intelligent learning environments. We recognise that in the educational technology field, theory development and system-design should be integrated and rely on an iterative process that addresses: (a) the difficulty to elicit precise, concise, and operationalized knowledge from "experts" and (b)…
Descriptors: Educational Technology, Methods, Expertise, Case Studies
Chong, Stefanie Xinyi; Lee, Chien-Sing – Educational Technology Research and Development, 2012
There are many evidences of motivational and educational benefits from the use of learning software. However, there is a lack of study with regards to the teaching of creative writing. This paper aims to bridge the following gaps: first, the need for a proper framework for scaffolding creative writing through learning software; second, the lack of…
Descriptors: Story Grammar, Creativity, Creative Writing, Educational Benefits