E-Collaborative Learning (e-CL)

2018 ◽  
pp. 6336-6346
Author(s):  
Alexandros Xafopoulos
Keyword(s):  
Collaborative Learning ◽  
Learning Theories ◽  
Design Element ◽  
Learning Content ◽  
Time Space ◽  
The Media ◽  
Addie Model ◽  
Five Phases ◽  
Media Applications

This article investigates the highly topical issue of electronic collaborative learning (e-CL) in a holistic overview. First of all, a clarification of the term and context of e-CL is provided comparing it with similar concepts. Second, the human elements and communities of e-CL are examined, together with their roles and aspects. Third, the supportive learning elements technology, pedagogy, and methodology are visited, exploring the media, applications, environments, infrastructure, learner modelling, learning objectives, major learning theories, methodological activities, and the learning content and its modalities. Fourth, the framework elements time, space, and society are described and a classification of e-CL approaches according to them is provided. Fifth, the e-CL process is examined following the ADDIE model and analysing its five phases and the design element hierarchy. Finally, future directions of e-CL are considered and conclusions are reached. Throughout the article key and significant approaches, methods, and terms are pinpointed and concisely developed.

E-Collaborative Learning (e-CL)

2019 ◽  
pp. 780-792
Author(s):  
Alexandros Xafopoulos
Keyword(s):  
Collaborative Learning ◽  
Learning Theories ◽  
Design Element ◽  
Learning Content ◽  
Time Space ◽  
The Media ◽  
Addie Model ◽  
Five Phases ◽  
Media Applications

This chapter investigates the highly topical issue of electronic collaborative learning (e-CL) in a holistic overview. First of all, a clarification of the term and context of e-CL is provided comparing it with similar concepts. Second, the human elements and communities of e-CL are examined, together with their roles and aspects. Third, the supportive learning elements—technology, pedagogy, and methodology—are visited, exploring the media, applications, environments, infrastructure, learner modelling, learning objectives, major learning theories, methodological activities, and the learning content and its modalities. Fourth, the framework elements—time, space, and society—are described and a classification of e-CL approaches according to them is provided. Fifth, the e-CL process is examined following the ADDIE model, analyzing its five phases and the design element hierarchy. Finally, future directions of e-CL are considered, and conclusions are reached. Throughout the chapter, key and significant approaches, methods, and terms are pinpointed and concisely developed.

E-Collaborative Learning (e-CL)

2016 ◽  
pp. 114-146 ◽  
Author(s):  
Alexandros Xafopoulos
Keyword(s):  
Collaborative Learning ◽  
Learning Process ◽  
Functional Categories ◽  
Future Directions ◽  
New Approaches ◽  
Time Space ◽  
Electronic Collaboration ◽  
Addie Model ◽  
Technology Pedagogy

This chapter investigates the highly researched and debated key issue of electronic collaboration (e-collaboration) in the learning process, onwards called e-collaborative learning (e-CL), in a holistic overview. The structure of the chapter is as follows. First of all, it clarifies the meaning and context of e-CL, and compares it with analysed relevant notions. Second, the human elements of e-CL and their roles are explored, classified into functional categories. Third, the supportive elements technology, pedagogy, and methodology are extensively visited. Fourth, the framework elements time, space, and society are presented. Fifth, the e-CL process is analysed, following the ADDIE model and analysing its phases. Sixth, significant affordances and challenges of e-CL are identified, and seventh, future directions are considered. Finally, conclusions are reached. Throughout the chapter new approaches, methods, and terms are proposed in the interests of the enrichment or the effectiveness of e-CL.

scholarly journals Mobile Game-Based Learning (mGBL): Application Development and Heuristics Evaluation Strategy

2010 ◽  
Author(s):  
Syamsul Bahrin Zaibon ◽  
Norshuhada Shiratuddin
Keyword(s):  
Design Research ◽  
Learning Theories ◽  
Research Approach ◽  
Game Based Learning ◽  
Application Development ◽  
Mobile Game ◽  
Evaluation Strategy ◽  
Learning Content ◽  
Game Developers ◽  
Five Phases

Purpose – This article presents an approach to developing a mobile game-based learning (mGBL) application by adapting unified characteristics of learning theories and approaches. In addition, the study also identified the strategy to evaluate mGBL.   Method – The study utilized the design research approach in information systems. The research methodology can be divided into five phases; (i) awareness of problem (ii) suggestion (iii) development (iv) evaluation and (v) conclusion.   Findings – Unified characteristics of mGBL were identified. In adapting the characteristics, the mGBL application was developed based on the concept of values in 1Malaysia. To evaluate the mGBL, a heuristics evaluation strategy is proposed. The strategy consists of four components: Game Usability, Mobility, Game Play, and Learning Content. Each of the components represents the issues to be considered and evaluated for a mGBL.   Value – The study provides intensive review of mGBL characteristics that can be useful and may be of interest to game developers. In addition the heuristics evaluation strategy is developed for evaluating the effectiveness of mGBL application.  

scholarly journals Pengembangan Media Monopoli Matematika pada Materi Peluang untuk Siswa SMP

2018 ◽  
Vol 3 (2) ◽  
pp. 114-131
Author(s):  
Desya Rossa Deviana ◽  
Erlina Prihatnani
Keyword(s):  
Junior High School ◽  
Field Trials ◽  
Average Score ◽  
Design Development ◽  
Mathematical Probability ◽  
Student Questionnaire ◽  
The Media ◽  
Addie Model ◽  
Five Phases ◽  
Total Average

This study aims to develop Monopoly Mathematics Media (Monomath) to learning mathematical probability exercises at junior high school. Using the ADDIE model consist of five phases - Analyze, Design, Development, Implementation, and Evaluation to develop this Monomath Media. This Monomath has gone through validity, practicability, and effectiveness test. The result of this research showed that the Monomath obtained a total average score for all aspect were 78.1% of validity matter expert and 80.8% of validity media expert, which means the media is valid. In the feasibility, the study result obtained a total average score for all aspect was 82.5%, which means the media has met practical criteria. The field trials result were obtained an average score of 95.46 for the posttest. It is higher than pretest average score was 54.83. The result of the student questionnaire showed that an average score of 90% which means the student give a positive response to the Monomath they used. Thus, the result of Monomath to learning mathematical probability is valid, practical, and effective.

E-Collaborative Learning (e-CL)

2017 ◽  
pp. 536-568
Author(s):  
Alexandros Xafopoulos
Keyword(s):  
Collaborative Learning ◽  
Learning Process ◽  
Functional Categories ◽  
Future Directions ◽  
New Approaches ◽  
Time Space ◽  
Electronic Collaboration ◽  
Addie Model ◽  
Technology Pedagogy

This chapter investigates the highly researched and debated key issue of electronic collaboration (e-collaboration) in the learning process, onwards called e-collaborative learning (e-CL), in a holistic overview. The structure of the chapter is as follows. First of all, it clarifies the meaning and context of e-CL, and compares it with analysed relevant notions. Second, the human elements of e-CL and their roles are explored, classified into functional categories. Third, the supportive elements technology, pedagogy, and methodology are extensively visited. Fourth, the framework elements time, space, and society are presented. Fifth, the e-CL process is analysed, following the ADDIE model and analysing its phases. Sixth, significant affordances and challenges of e-CL are identified, and seventh, future directions are considered. Finally, conclusions are reached. Throughout the chapter new approaches, methods, and terms are proposed in the interests of the enrichment or the effectiveness of e-CL.

scholarly journals Developing the fun and educative module in plant morphology and anatomy learning for tenth graders

2018 ◽  
Vol 4 (1) ◽  
pp. 53
Author(s):  
Alfi Suciyati ◽  
Tabita Adian
Keyword(s):  
Plant Morphology ◽  
Learning Material ◽  
Design Development ◽  
Tenth Graders ◽  
Teachers And Students ◽  
The Media ◽  
Addie Model ◽  
Data Collection Technique ◽  
Five Phases ◽  
Descriptive Qualitative

This research aims to examine the eligibility of and responses from expert media, expert material, practitioners and students’ on the ‘Fun and Educative’ biology module. The module was developed in a fun and educative way presenting various educative games. The research development model is using ADDIE model that consists of five phases: Analysis, Design, Development, Implementation, and Evaluation. The data collection technique employed examination of learning media experts, material experts, practitioners (biology teachers), and students. The data of research was analyzed in descriptive-qualitative and descriptive-qualitative ways. The results of evaluation on the module’s eligibility convey that the learning media expert gave 87.69% with the category of ‘highly eligible’, the material expert gave 86.00% with the category of ‘highly eligible', and the practitioners gave 83.68% with the category of ‘eligible'. The students' responses to questionnaires given related to the developed module gave 90.00% with the category of ‘highly interesting'. Based on the results of examination by the media expert, material expert, practitioners, and students, conclude that the module has fulfilled the criteria of good and eligible learning material and can be used for studying biology.

Developing a Pop Up Book Supportive to Narrative-Texts Teaching

2019 ◽  
Vol 1 (2) ◽  
pp. 66
Author(s):  
Khoirunnisa Safitri ◽  
Sudarsono Sudarsono
Keyword(s):  
Narrative Text ◽  
Development Phase ◽  
Design Phase ◽  
Narrative Texts ◽  
Evaluation Result ◽  
Tenth Grade ◽  
Text Reading ◽  
The Media ◽  
Addie Model ◽  
Teaching Learning

This research aims to develop Pop-Up Book as supplementary media to support the teaching of narrative texts and to evaluate whether or not the media are feasible to teach narrative texts to the tenth grade students of SMA Negeri 8 Pontianak. The media consisted of narrative texts with pop-up pictures. They were divided based on the structure of a narrative text. The materials were taken from the students’ textbook that the researcher has simplified. The procedures were adapted from ADDIE Model proposed by Branch and it used three phases, namely, Analyse, Design, and Develop. From analyse phase, it was found that the students needed interesting media that was visually attractive to engage them in the teaching learning process and to support the existing materials. The Design phase covered the aspects, which were the focus of the media, of the materials and the pictures for the media, and the structure of the media. The Development phase concerned the development of the essential parts of the media. According to the evaluation result, the media are considered feasible to be applied by the teachers to teach narrative text reading.

scholarly journals Time–frequency time–space LSTM for robust classification of physiological signals

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tuan D. Pham
Keyword(s):  
Time Series ◽  
Network Architecture ◽  
Time Series Data ◽  
Short Term Memory ◽  
Physiological Signals ◽  
Series Data ◽  
Time Frequency ◽  
Time Space ◽  
Deep Recurrent Neural Network

AbstractAutomated analysis of physiological time series is utilized for many clinical applications in medicine and life sciences. Long short-term memory (LSTM) is a deep recurrent neural network architecture used for classification of time-series data. Here time–frequency and time–space properties of time series are introduced as a robust tool for LSTM processing of long sequential data in physiology. Based on classification results obtained from two databases of sensor-induced physiological signals, the proposed approach has the potential for (1) achieving very high classification accuracy, (2) saving tremendous time for data learning, and (3) being cost-effective and user-comfortable for clinical trials by reducing multiple wearable sensors for data recording.

scholarly journals Towards modeling of human skilling for electrical circuitry using augmented reality applications

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Ana Villanueva ◽  
Ziyi Liu ◽  
Yoshimasa Kitaguchi ◽  
Zhengzhe Zhu ◽  
Kylie Peppler ◽  
...  
Keyword(s):  
Augmented Reality ◽  
Learning Outcomes ◽  
Cognitive Assessment ◽  
Teaching And Learning ◽  
Stem Learning ◽  
Educational Value ◽  
Learning Content ◽  
Hands On ◽  
Specific Learning

AbstractAugmented reality (AR) is a unique, hands-on tool to deliver information. However, its educational value has been mainly demonstrated empirically so far. In this paper, we present a modeling approach to provide users with mastery of a skill, using AR learning content to implement an educational curriculum. We illustrate the potential of this approach by applying this to an important but pervasively misunderstood area of STEM learning, electrical circuitry. Unlike previous cognitive assessment models, we break down the area into microskills—the smallest segmentation of this knowledge—and concrete learning outcomes for each. This model empowers the user to perform a variety of tasks that are conducive to the acquisition of the skill. We also provide a classification of microskills and how to design them in an AR environment. Our results demonstrated that aligning the AR technology to specific learning objectives paves the way for high quality assessment, teaching, and learning.

scholarly journals Time-frequency time-space long short-term memory networks for image classification of histopathological tissue

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tuan D. Pham
Keyword(s):  
Image Analysis ◽  
Short Term Memory ◽  
Disease Diagnosis ◽  
Short Term ◽  
Term Memory ◽  
Time Frequency ◽  
Time Space ◽  
Histopathological Images ◽  
Long Short Term Memory

AbstractImage analysis in histopathology provides insights into the microscopic examination of tissue for disease diagnosis, prognosis, and biomarker discovery. Particularly for cancer research, precise classification of histopathological images is the ultimate objective of the image analysis. Here, the time-frequency time-space long short-term memory network (TF-TS LSTM) developed for classification of time series is applied for classifying histopathological images. The deep learning is empowered by the use of sequential time-frequency and time-space features extracted from the images. Furthermore, unlike conventional classification practice, a strategy for class modeling is designed to leverage the learning power of the TF-TS LSTM. Tests on several datasets of histopathological images of haematoxylin-and-eosin and immunohistochemistry stains demonstrate the strong capability of the artificial intelligence (AI)-based approach for producing very accurate classification results. The proposed approach has the potential to be an AI tool for robust classification of histopathological images.

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