The Experts below are selected from a list of 18264 Experts worldwide ranked by ideXlab platform

Javad Hatami - One of the best experts on this subject based on the ideXlab platform.

  • Computer-Supported Collaborative Concept-Mapping: The Effects of Different Instructional Designs on Conceptual Understanding and Knowledge Co-Construction
    2020
    Co-Authors: Mohammadreza Farrokhnia, Héctor J. Pijeira-díaz, Omid Noroozi, Javad Hatami
    Abstract:

    This article investigated the effect of different Instructional Designs using CSCCM on students’ conceptual understanding, and on the quality of students’ knowledge co-construction. Hundred-twenty 10th graders randomly distributed in dyads. They were asked to draw concept maps by using CSCCM with different Instructional Designs. In the control condition, dyads worked collaboratively all the time. In both Exp.1 and Exp.2,dyads worked first individually and then collaboratively. In Exp.2, the individual concept map was shared with the peer before collaborating. Conceptual understanding improved for all learners in three conditions, especially in Exp.2. Statistically significant differences were found in students’ knowledge co-construction among the three conditions. Accordingly, an Instructional design like Exp.2 optimizes CSCCM learning outcomes in terms of conceptual understanding and knowledge co-construction.

  • Computer-supported collaborative concept mapping: The effects of different Instructional Designs on conceptual understanding and knowledge co-construction
    Computers & Education, 2019
    Co-Authors: Mohammadreza Farrokhnia, Héctor J. Pijeira-díaz, Omid Noroozi, Javad Hatami
    Abstract:

    Abstract Computer-supported collaborative concept mapping (CSCCM) leverages technology and concept mapping to support conceptual understanding, as well as collaborative learning to foster knowledge co-construction. This article investigated the effect of different Instructional Designs using CSCCM on students' conceptual understanding, and on the type of processes of knowledge co-construction that students engage. Participants (N = 120) were 10th graders enrolled in their physics course, randomly distributed in dyads. They were asked to draw concept maps related to the conservation of energy law, by using CSCCM with different Instructional Designs (i.e., control, Exp. 1 and Exp. 2). In the control condition, dyads worked collaboratively all the time. In both Exp. 1 and Exp. 2, dyads worked first individually (one week) and then collaboratively (two weeks). However, in Exp. 2, the individual concept map was shared with the peer before collaborating. Conceptual understanding improved significantly for learners in all three experimental conditions, especially in Exp. 2. Statistically significant differences were found in students' knowledge co-construction among the three conditions. Dyads in the control group showed a significantly higher use of quick consensus-building. Dyads in Exp. 1 showed a significantly higher reliance on externalization and elicitation. Dyads in Exp. 2 showed a significantly higher enacting of integration- and conflict-oriented consensus building. Accordingly, an Instructional design like Exp. 2 optimizes CSCCM learning outcomes in terms of conceptual understanding and knowledge co-construction.

Kesav V. Nori - One of the best experts on this subject based on the ideXlab platform.

  • A patterns based approach for the design of educational technologies
    Interactive Learning Environments, 2021
    Co-Authors: Sridhar Chimalakonda, Kesav V. Nori
    Abstract:

    Despite rapid advances, modeling a variety of Instructional Designs to support variations in teaching and learning during the design of educational technologies is still an open challenge. In this ...

  • An ontology based modeling framework for design of educational technologies
    Smart Learning Environments, 2020
    Co-Authors: Sridhar Chimalakonda, Kesav V. Nori
    Abstract:

    Despite rapid progress, most of the educational technologies today lack a strong Instructional design knowledge basis leading to questionable quality of instruction. In addition, a major challenge is to customize these educational technologies for a wide range of customizable Instructional Designs. Ontologies are one of the pertinent mechanisms to represent Instructional design in the literature. However, existing approaches do not support modeling of flexible Instructional Designs. To address this problem, in this paper, we propose an ontology based framework for systematic modeling of different aspects of Instructional design knowledge based on domain patterns. As part of the framework, we present ontologies for modeling goals , Instructional processes and Instructional material . We demonstrate the ontology framework by presenting instances of the ontology for the large scale case study of adult literacy in India (287 million learners spread across 22 Indian Languages), which requires creation of hundreds of similar but varied e Learning Systems based on flexible Instructional Designs. The implemented framework is available at http://rice.iiit.ac.in and is transferred to National Literacy Mission Authority of Government of India . The proposed framework could be potentially used for modeling Instructional design knowledge for school education, vocational skills and beyond.

  • A family of software product lines in educational technologies
    Computing, 2020
    Co-Authors: Sridhar Chimalakonda, Kesav V. Nori
    Abstract:

    Rapid advances in education domain demand the design and customization of educational technologies for a large scale and variety of evolving requirements. Here, scale is the number of systems to be developed and variety stems from a diversified range of Instructional Designs such as varied goals, processes, content, teaching styles, learning styles and, also for eLearning Systems for 22 Indian Languages and variants. In this paper, we present a family of software product lines as an approach to address this challenge of modeling a family of Instructional Designs as well as a family of e Learning Systems and demonstrate it for the case of adult literacy in India (287 million learners). We present a multi-level product line that connects product lines at multiple levels of granularity in education domain. We then detail two concrete product lines ( http://rice.iiit.ac.in ), one that generates Instructional design editors and two, which generates a family of e Learning Systems based on flexible Instructional Designs. Finally, we demonstrate our approach by generating e Learning Systems for Hindi and Telugu languages, which led to significant cost savings of 29 person-months for 9 e Learning Systems.

  • A Family of Software Product Lines in Educational Technologies
    arXiv: Software Engineering, 2018
    Co-Authors: Sridhar Chimalakonda, Kesav V. Nori
    Abstract:

    Rapid advances in education domain demand the design and customization of educational technologies for a large scale and variety of evolving requirements. Here, scale is the number of systems to be developed and variety stems from a diversified range of Instructional Designs such as varied goals, processes, content, teacher styles, learner styles and, also for eLearning Systems for 22 Indian Languages and variants. In this paper, we present a family of software product lines as an approach to address this challenge of modeling a family of Instructional Designs as well as a family of eLearning Systems and demonstrate it for the case of adult literacy in India (287 million learners). We present a multi-level product line that connects product lines at multiple levels of granularity in education domain. We then detail two concrete product lines (this http URL), one that generates Instructional design editors and two, which generates a family of eLearning Systems based on flexible Instructional Designs. Finally, we demonstrate our approach by generating eLearning Systems for Hindi and Telugu languages (both web and android versions), which led to significant cost savings of 29 person months for 9 eLearning Systems.

  • An Ontology Based Modeling Framework for Design of Educational Technologies
    arXiv: Computers and Society, 2018
    Co-Authors: Sridhar Chimalakonda, Kesav V. Nori
    Abstract:

    Despite rapid progress, most of the educational technologies today lack a strong Instructional design knowledge basis leading to questionable quality of instruction. In addition, a major challenge is to customize these educational technologies for a wide range of Instructional Designs. Ontologies are one of the pertinent mechanisms to represent Instructional design in the literature. However, existing approaches do not support modeling of flexible Instructional Designs. To address this problem, in this paper, we propose an ontology based framework for systematic modeling of different aspects of Instructional design knowledge based on domain patterns. As part of the framework, we present ontologies for modeling goals, Instructional processes and Instructional materials. We demonstrate the ontology framework by presenting instances of the ontology for the large scale case study of adult literacy in India (287 million learners spread across 22 Indian Languages), which requires creation of 1000 similar but varied eLearning Systems based on flexible Instructional Designs. The implemented framework is available at this http URL and is transferred to National Literacy Mission of Government of India. This framework could be used for modeling Instructional design knowledge of systems for skills, school education and beyond.

Mohammadreza Farrokhnia - One of the best experts on this subject based on the ideXlab platform.

  • Computer-Supported Collaborative Concept-Mapping: The Effects of Different Instructional Designs on Conceptual Understanding and Knowledge Co-Construction
    2020
    Co-Authors: Mohammadreza Farrokhnia, Héctor J. Pijeira-díaz, Omid Noroozi, Javad Hatami
    Abstract:

    This article investigated the effect of different Instructional Designs using CSCCM on students’ conceptual understanding, and on the quality of students’ knowledge co-construction. Hundred-twenty 10th graders randomly distributed in dyads. They were asked to draw concept maps by using CSCCM with different Instructional Designs. In the control condition, dyads worked collaboratively all the time. In both Exp.1 and Exp.2,dyads worked first individually and then collaboratively. In Exp.2, the individual concept map was shared with the peer before collaborating. Conceptual understanding improved for all learners in three conditions, especially in Exp.2. Statistically significant differences were found in students’ knowledge co-construction among the three conditions. Accordingly, an Instructional design like Exp.2 optimizes CSCCM learning outcomes in terms of conceptual understanding and knowledge co-construction.

  • Computer-supported collaborative concept mapping: The effects of different Instructional Designs on conceptual understanding and knowledge co-construction
    Computers & Education, 2019
    Co-Authors: Mohammadreza Farrokhnia, Héctor J. Pijeira-díaz, Omid Noroozi, Javad Hatami
    Abstract:

    Abstract Computer-supported collaborative concept mapping (CSCCM) leverages technology and concept mapping to support conceptual understanding, as well as collaborative learning to foster knowledge co-construction. This article investigated the effect of different Instructional Designs using CSCCM on students' conceptual understanding, and on the type of processes of knowledge co-construction that students engage. Participants (N = 120) were 10th graders enrolled in their physics course, randomly distributed in dyads. They were asked to draw concept maps related to the conservation of energy law, by using CSCCM with different Instructional Designs (i.e., control, Exp. 1 and Exp. 2). In the control condition, dyads worked collaboratively all the time. In both Exp. 1 and Exp. 2, dyads worked first individually (one week) and then collaboratively (two weeks). However, in Exp. 2, the individual concept map was shared with the peer before collaborating. Conceptual understanding improved significantly for learners in all three experimental conditions, especially in Exp. 2. Statistically significant differences were found in students' knowledge co-construction among the three conditions. Dyads in the control group showed a significantly higher use of quick consensus-building. Dyads in Exp. 1 showed a significantly higher reliance on externalization and elicitation. Dyads in Exp. 2 showed a significantly higher enacting of integration- and conflict-oriented consensus building. Accordingly, an Instructional design like Exp. 2 optimizes CSCCM learning outcomes in terms of conceptual understanding and knowledge co-construction.

Sridhar Chimalakonda - One of the best experts on this subject based on the ideXlab platform.

  • A patterns based approach for the design of educational technologies
    Interactive Learning Environments, 2021
    Co-Authors: Sridhar Chimalakonda, Kesav V. Nori
    Abstract:

    Despite rapid advances, modeling a variety of Instructional Designs to support variations in teaching and learning during the design of educational technologies is still an open challenge. In this ...

  • An ontology based modeling framework for design of educational technologies
    Smart Learning Environments, 2020
    Co-Authors: Sridhar Chimalakonda, Kesav V. Nori
    Abstract:

    Despite rapid progress, most of the educational technologies today lack a strong Instructional design knowledge basis leading to questionable quality of instruction. In addition, a major challenge is to customize these educational technologies for a wide range of customizable Instructional Designs. Ontologies are one of the pertinent mechanisms to represent Instructional design in the literature. However, existing approaches do not support modeling of flexible Instructional Designs. To address this problem, in this paper, we propose an ontology based framework for systematic modeling of different aspects of Instructional design knowledge based on domain patterns. As part of the framework, we present ontologies for modeling goals , Instructional processes and Instructional material . We demonstrate the ontology framework by presenting instances of the ontology for the large scale case study of adult literacy in India (287 million learners spread across 22 Indian Languages), which requires creation of hundreds of similar but varied e Learning Systems based on flexible Instructional Designs. The implemented framework is available at http://rice.iiit.ac.in and is transferred to National Literacy Mission Authority of Government of India . The proposed framework could be potentially used for modeling Instructional design knowledge for school education, vocational skills and beyond.

  • A family of software product lines in educational technologies
    Computing, 2020
    Co-Authors: Sridhar Chimalakonda, Kesav V. Nori
    Abstract:

    Rapid advances in education domain demand the design and customization of educational technologies for a large scale and variety of evolving requirements. Here, scale is the number of systems to be developed and variety stems from a diversified range of Instructional Designs such as varied goals, processes, content, teaching styles, learning styles and, also for eLearning Systems for 22 Indian Languages and variants. In this paper, we present a family of software product lines as an approach to address this challenge of modeling a family of Instructional Designs as well as a family of e Learning Systems and demonstrate it for the case of adult literacy in India (287 million learners). We present a multi-level product line that connects product lines at multiple levels of granularity in education domain. We then detail two concrete product lines ( http://rice.iiit.ac.in ), one that generates Instructional design editors and two, which generates a family of e Learning Systems based on flexible Instructional Designs. Finally, we demonstrate our approach by generating e Learning Systems for Hindi and Telugu languages, which led to significant cost savings of 29 person-months for 9 e Learning Systems.

  • A Family of Software Product Lines in Educational Technologies
    arXiv: Software Engineering, 2018
    Co-Authors: Sridhar Chimalakonda, Kesav V. Nori
    Abstract:

    Rapid advances in education domain demand the design and customization of educational technologies for a large scale and variety of evolving requirements. Here, scale is the number of systems to be developed and variety stems from a diversified range of Instructional Designs such as varied goals, processes, content, teacher styles, learner styles and, also for eLearning Systems for 22 Indian Languages and variants. In this paper, we present a family of software product lines as an approach to address this challenge of modeling a family of Instructional Designs as well as a family of eLearning Systems and demonstrate it for the case of adult literacy in India (287 million learners). We present a multi-level product line that connects product lines at multiple levels of granularity in education domain. We then detail two concrete product lines (this http URL), one that generates Instructional design editors and two, which generates a family of eLearning Systems based on flexible Instructional Designs. Finally, we demonstrate our approach by generating eLearning Systems for Hindi and Telugu languages (both web and android versions), which led to significant cost savings of 29 person months for 9 eLearning Systems.

  • An Ontology Based Modeling Framework for Design of Educational Technologies
    arXiv: Computers and Society, 2018
    Co-Authors: Sridhar Chimalakonda, Kesav V. Nori
    Abstract:

    Despite rapid progress, most of the educational technologies today lack a strong Instructional design knowledge basis leading to questionable quality of instruction. In addition, a major challenge is to customize these educational technologies for a wide range of Instructional Designs. Ontologies are one of the pertinent mechanisms to represent Instructional design in the literature. However, existing approaches do not support modeling of flexible Instructional Designs. To address this problem, in this paper, we propose an ontology based framework for systematic modeling of different aspects of Instructional design knowledge based on domain patterns. As part of the framework, we present ontologies for modeling goals, Instructional processes and Instructional materials. We demonstrate the ontology framework by presenting instances of the ontology for the large scale case study of adult literacy in India (287 million learners spread across 22 Indian Languages), which requires creation of 1000 similar but varied eLearning Systems based on flexible Instructional Designs. The implemented framework is available at this http URL and is transferred to National Literacy Mission of Government of India. This framework could be used for modeling Instructional design knowledge of systems for skills, school education and beyond.

Omid Noroozi - One of the best experts on this subject based on the ideXlab platform.

  • Computer-Supported Collaborative Concept-Mapping: The Effects of Different Instructional Designs on Conceptual Understanding and Knowledge Co-Construction
    2020
    Co-Authors: Mohammadreza Farrokhnia, Héctor J. Pijeira-díaz, Omid Noroozi, Javad Hatami
    Abstract:

    This article investigated the effect of different Instructional Designs using CSCCM on students’ conceptual understanding, and on the quality of students’ knowledge co-construction. Hundred-twenty 10th graders randomly distributed in dyads. They were asked to draw concept maps by using CSCCM with different Instructional Designs. In the control condition, dyads worked collaboratively all the time. In both Exp.1 and Exp.2,dyads worked first individually and then collaboratively. In Exp.2, the individual concept map was shared with the peer before collaborating. Conceptual understanding improved for all learners in three conditions, especially in Exp.2. Statistically significant differences were found in students’ knowledge co-construction among the three conditions. Accordingly, an Instructional design like Exp.2 optimizes CSCCM learning outcomes in terms of conceptual understanding and knowledge co-construction.

  • Computer-supported collaborative concept mapping: The effects of different Instructional Designs on conceptual understanding and knowledge co-construction
    Computers & Education, 2019
    Co-Authors: Mohammadreza Farrokhnia, Héctor J. Pijeira-díaz, Omid Noroozi, Javad Hatami
    Abstract:

    Abstract Computer-supported collaborative concept mapping (CSCCM) leverages technology and concept mapping to support conceptual understanding, as well as collaborative learning to foster knowledge co-construction. This article investigated the effect of different Instructional Designs using CSCCM on students' conceptual understanding, and on the type of processes of knowledge co-construction that students engage. Participants (N = 120) were 10th graders enrolled in their physics course, randomly distributed in dyads. They were asked to draw concept maps related to the conservation of energy law, by using CSCCM with different Instructional Designs (i.e., control, Exp. 1 and Exp. 2). In the control condition, dyads worked collaboratively all the time. In both Exp. 1 and Exp. 2, dyads worked first individually (one week) and then collaboratively (two weeks). However, in Exp. 2, the individual concept map was shared with the peer before collaborating. Conceptual understanding improved significantly for learners in all three experimental conditions, especially in Exp. 2. Statistically significant differences were found in students' knowledge co-construction among the three conditions. Dyads in the control group showed a significantly higher use of quick consensus-building. Dyads in Exp. 1 showed a significantly higher reliance on externalization and elicitation. Dyads in Exp. 2 showed a significantly higher enacting of integration- and conflict-oriented consensus building. Accordingly, an Instructional design like Exp. 2 optimizes CSCCM learning outcomes in terms of conceptual understanding and knowledge co-construction.