scholarly journals Factors of Online Learning Model to Enhance Knowledge Construction in Multicultural Society for Workers Competencies in Southernmost Provinces of Thailand

2018 ◽  
Vol 8 (12) ◽  
pp. 918-921
Author(s):  
Anuchit Ngamkajornwiwat ◽  
◽  
Wasant Atisabda ◽  
Ophat Kaosaiyaporn
Keyword(s):  
Online Learning ◽  
Knowledge Construction ◽  
Learning Model ◽  
Multicultural Society

Enlivening the Promise of Education

2009 ◽  
pp. 257-279
Author(s):  
Kuldip Kaur
Keyword(s):  
Online Learning ◽  
Human Computer Interaction ◽  
Knowledge Construction ◽  
Learning Model ◽  
Open University ◽  
Online Interaction ◽  
Social Environments ◽  
Learning Contexts ◽  
Face To Face Learning ◽  
Computer Interaction

An important dimension in education is interaction, that is, the coming together of a number of people to discuss, debate, and deliberate about issues of common concern. In distance education, such social environments are as much present in online learning contexts as they are in face-to-face learning contexts such as tutorials. This chapter expands the notion of teacher-student interaction to focus on integrating human computer interaction in the curriculum. This is done through the use of online discussion forums at Open University Malaysia that help build collaborative online communities using common principles of teaching and learning. Citing a recent case in point, this chapter demonstrates how the Open University Malaysia-Collaborative Online Learning Model for online interaction helped cultivate learner-centric virtual discussions and supported an interactive online community that showcased characteristics of social interdependence and instructional support. This chapter takes a social constructivist view of human computer interaction by proposing an instructional model supported by collaboration, guidance, interdependence, cognitive challenge, knowledge construction, and knowledge extension. The Introduction section of this chapter provides the rationale for human computer interaction and gives an overview of current-day perspectives on the online classroom. This is followed by a trenchant review of recent research on online interaction with a view to outlining the theoretical premise for the use of computers to develop thinking and collaborative or team skills. This section also provides a rationale for the use of online forums and gives a frame of reference for the role of the instructor in this enterprise. In the next section of this chapter, the Open University Malaysia-collaborative online learning model is described, with details on The Learning Context as well as Group Learning Outcomes, which may be seen as inherent parts of the model. Under the sub-section Knowledge Construction, the chapter carries a qualitative analysis of online interaction for one Open University Malaysia course using a comprehensive list of indigenous categories and sub-categories as well as examples of interactions that match each sub-category. The chapter ends with a Summary, a statement of Acknowledgement, a list of References, and an Appendix. The appendix contains the Task that was used for the course for which online interaction in this chapter was analyzed.

Enlivening the Promise of Education

2007 ◽  
pp. 132-153 ◽  
Author(s):  
K. Kaur
Keyword(s):  
Online Learning ◽  
Human Computer Interaction ◽  
Knowledge Construction ◽  
Learning Model ◽  
Open University ◽  
Online Interaction ◽  
Social Environments ◽  
Learning Contexts ◽  
Face To Face Learning ◽  
Computer Interaction

An important dimension in education is interaction, that is, the coming together of a number of people to discuss, debate, and deliberate about issues of common concern. In distance education, such social environments are as much present in online learning contexts as they are in face-to-face learning contexts such as tutorials. This chapter expands the notion of teacher student interaction to focus on integrating human computer interaction in the curriculum. This is done through the use of online discussion forums at Open University Malaysia that help build collaborative online communities using common principles of teaching and learning. Citing a recent case in point, this chapter demonstrates how the Open University Malaysia-Collaborative Online Learning Model for online interaction helped cultivate learner-centric virtual discussions and supported an interactive online community that showcased characteristics of social interdependence and instructional support. This chapter takes a social constructivist view of human computer interaction by proposing an instructional model supported by collaboration, guidance, interdependence, cognitive challenge, knowledge construction, and knowledge extension. The Introduction section of this chapter provides the rationale for human computer interaction and gives an overview of current-day perspectives on the online classroom. This is followed by a trenchant review of recent research on online interaction with a view to outlining the theoretical premise for the use of computers to develop thinking and collaborative or team skills. This section also provides a rationale for the use of online forums and gives a frame of reference for the role of the instructor in this enterprise. In the next section of this chapter, the Open University Malaysia-collaborative online learning model is described, with details on The Learning Context as well as Group Learning Outcomes, which may be seen as inherent parts of the model. Under the sub-section Knowledge Construction, the chapter carries a qualitative analysis of online interaction for one Open University Malaysia course using a comprehensive list of indigenous categories and sub-categories as well as examples of interactions that match each sub-category. The chapter ends with a Summary, a statement of Acknowledgement, a list of References, and an Appendix. The appendix contains the Task that was used for the course for which online interaction in this chapter was analyzed.

scholarly journals Research on the differences of students’ learning styles and knowledge integration in SPOC learning: a case study of course “Basic Portuguese”

2021 ◽  
Vol 18 (1) ◽  
pp. 12-26
Author(s):  
Jing Hu ◽  
Silva Maria Do Carmo Vieira
Keyword(s):  
Online Learning ◽  
Learning Styles ◽  
Learning Style ◽  
Knowledge Construction ◽  
Knowledge Integration ◽  
Teaching Method ◽  
Integration Theory ◽  
Online Data ◽  
Learning Behaviors ◽  
Learning Platform

Problem and goal. With the advent of the information age, Internet-based online learning has also become one of the learning methods chosen by many learners. They can use these online learning platforms to complete knowledge construction while learning offline. Methodology. Most studies of learning behaviors focus on the discovery of the best learning model and disregard the possible impact of different learning behaviors on knowledge construction. Therefore, based on the Felder - Silverman learning style model, this article uses the Solomon learning style scale to improve the design of the questionnaire and collect four-dimensional differential learning behaviors data. In order to further understand the influence of learning styles on the effectiveness of online learning, we also use online learning data on the Small Private Online Course platform and general cognitive intelligence knowledge integration theory to clarify the relation between learning modes and individuals differences. Results. This study observes and analyzes the learning behavior data of 46 students of Nankai University in the SPOC learning platform, also analyzes the differences in learning styles and knowledge construction of students in the SPOC environment. Compared with the traditional Basic Portuguese teaching method, the blended teaching model based on the Chaoxing Learning platform has unparalleled advantages. Interactions inside and outside the classroom, improving student participation and promoting teaching diagnosis. Conclusion. Through a comprehensive analysis of questionnaire data and online data, we found that some learning styles have different effects on the effectiveness of online learning, ignoring the individual differences of learners will still cause problems in knowledge construction.

scholarly journals PENGARUH MODEL PEMBELAJARAN LURING DAN MODEL PEMBELAJARAN DARING TERHADAP PRESTASI BELAJAR SISWA METTA SCHOOL

2021 ◽  
Vol 35 (2) ◽  
pp. 105-113
Author(s):  
Wina Dhamayanti ◽  
Silvya Indraningtyas ◽  
Adji Sastrosupadi
Keyword(s):  
Elementary School ◽  
Online Learning ◽  
Elementary School Students ◽  
Learning Model ◽  
Report Cards ◽  
School Students ◽  
Model Learning ◽  
Learning Achievement ◽  
Offline Learning ◽  
The Difference

Penelitian ini bertujuan untuk mengetahui perbedaan pengaruh antara model pembelajaran luring dan model pembelajaran daring terhadap prestasi belajar siswa SD Metta School Surabaya. Desain yang digunakan dalam penelitian berbentuk eksperimen dengan pendekatan kuantitatif. Instrumen yang digunakan dalam penelitian ini adalah angket yang disebarkan kepada 44 siswa SD dari kelas III-VI dan dokumen berupa nilai raport siswa. Data yang telah diperoleh dari penyebaran angket kemudian dianalisis menggunakan skala likert dan diuji dengan menggunakan uji-z. Hasil penelitian ini menunjukkan bahwa model pembelajaran luring dan model pembelajaran daring ada pengaruh terhadap prestasi belajar, jika ditinjau dari persen capaian sebesar 95% dan 79,75%. Selanjutnya berdasarkan uji-z diperoleh nilai signifikansi 6,827> , sehingga dapat disimpulkan bahwa ada pengaruh yang sangat nyata pada model pembelajaran luring dan model pembelajaran daring terhadap prestasi belajar. Jadi, peran guru dalam proses pembelajaran sangat penting untuk memancing motivasi belajar anak. Hal tersebut, juga harus didorong oleh usaha peserta didik dalam kegiatan belajar, sehingga pengalaman yang diperolehnya dapat memberikan manfaat dalam belajar. Kata-kata Kunci: Luring, Daring, Prestasi Belajar   Abstract: The study aims to determine the difference in the effect of offline learning model and online learning model on student achievement at Metta School Surabaya Elementary School. The design used in this research is in the form of an experiment with a quantitative approach. The instrument used in this study was a questionnaire distributed to 44 elementary school students from grades III-VI and a document in the form of student report cards. Data obtained from questionnaire distribution and then analyzed using a Likert scale and tested using the z-test. The results of this study indicate that the offline learning model and online learning model have an influence on learning achievement, when viewed from the percentage of achievement of 95% and 79,75%. Furthermore, based on the z-test, a significance value of 6,827>  was obtained, so it can be concluded that there is a very significance effect on the offline learning model and online learning model on learning achievement. Keywords: Offline Learning Model, Online Learning Model, Learning  Achievement

scholarly journals Brain-Based Online Learning Design in The Disruptive Era for Students in University

2021 ◽  
Vol 11 (6) ◽  
pp. 277
Author(s):  
Andi Kristanto ◽  
. Sulistiowati ◽  
Hirnanda Dimas Pradana
Keyword(s):  
Online Learning ◽  
Learning Process ◽  
Field Trials ◽  
Learning Model ◽  
Learning Design ◽  
Development Research ◽  
Design Development ◽  
Learning Materials ◽  
Percentage Score ◽  
The Brain

The learning model is a collection of activities that occur during the teaching and learning process with the objective of achieving the set goals. The brain-based online learning model developed is a solution to the students' learning problems. The majority of students struggle to interpret all of the learning materials they receive. This resulted in students' dissatisfaction with the learning materials. The purpose of this research is to develop a brain-based online learning process design based on the aforementioned problems. The Lee & Owens model of development was used in this development research. The stages of the Lee & Owens development model are analysis, design, development, implementation, and evaluation. The development research findings are as follows: (1) the media experts' assessment, which resulted in an 89.35% score with a valid category. (2) The assessment of the developed learning materials by material experts resulted in a score of 91.23% with a valid category. (3) expert evaluation, with an overall score of 86.35% for having a valid category. (4) The results of individual trials produced a percentage score of 88.5% with a valid category. (5) The results of small group trials indicated an overall percentage score of 81.60% of valid categories. (6) Field trials are classified as valid when they receive a percentage of 79.89%. The results of the development indicate that the brain-based online learning design is feasible for use.   Received: 11 August 2021 / Accepted: 27 October 2021 / Published: 5 November 2021

Dynamic Maps’ Use in Smart-Cities Learning Contexts

2012 ◽  
Vol 3 (4) ◽  
pp. 33-49
Author(s):  
Marco Pedroni
Keyword(s):  
Online Learning ◽  
Knowledge Construction ◽  
Smart Cities ◽  
Learning Objects ◽  
Constructivist Teaching ◽  
Reconstruction Algorithms ◽  
Dynamic Reconstruction ◽  
Learning Contexts ◽  
Animated Maps

This paper examines the potentialities and characteristics of dynamic maps in relationship with constructivist teaching, by considering maps’ support to four functions: the contents’ learning, the contextualization of Learning Objects, the contextualization of online learning interaction and the knowledge construction. Several algorithms for polymorphic and animated maps’ reconstruction, both bi-dimensional and tridimensional, will be examined and described in detail. Among these algorithms, a further differentiation is made between those concerning proximal, or hierarchical development, and those regarding gravitational developments. In the latter one the positioning of nodes derives from quantitative values, that express their relation’s attractive strength. Conclusions derived from this work are the unavoidable need to implement maps’ dynamic reconstruction algorithms, when the complexity of the disciplinary ontology makes the traditional static approaches unable to provide an effectively usable image of the map.

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