A heutagogical interactive tutorial involving Fishbowl with Fish Battle and Round Robin Brainstorming: A novel syndicate metacognitive learning strategy

Anand, Nirmala; Pujar, Somashekhar; Rao, Sakshi

doi:10.1016/j.mjafi.2020.12.003

Cited by 5 publications

(6 citation statements)

References 10 publications

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“…Several elements of Heutagogy approach are included on E-module, namely: (a) explore; (b) create; (c) collaborated; (d) connect; (e) share; (f) reflect (Blaschke & Hase, 2016;Mohamad et al, 2020). This study in line with previous research which stated that the use of teaching materials in the form of e-modules based on the heutagogy approach can improve student learning outcomes by using technology (Anand et al, 2021;Jazeel, 2016;Kamrozzaman et al, 2020).…”

Section: Discussionsupporting

confidence: 87%

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E-Module of Mathematics Economic Using Heutagogy Approach for Distance Learning: Is It Effective?

et al. 2022

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Heutagogy approach is the development of andragogy learning which focuses on students’ self-determined learning. This approach can be used as an alternative for distance learning. To support the learning process, an e-module based on heutagogy is needed. Therefore, the purpose of this study was to create and analyze the effectiveness of E-Module in Mathematics Economic based on the Heutagogy Approach in distance learning. Research design used 4-D model consists of define, design, develop, and desseminate stages. Examining the E-module effectiveness was using experiment research with one group pre-test-post-test design which involved 66 students of Economics Education as participants. Data collection are carried out with questionnaire and analyzed with several test, namely: Kolmogorov-Smirnov Normality Test, Wilcoxon signed-rank test.The results of this study revealed that: 1) E-module of mathematics economic using Heutagogy Approach feasible as learning media, 2) there is an effect of using E-module of Mathematics Economic using Heutagogy Approach for Distance Learning. E-module can increases students learning outcomes and helps them to study independently during distance learning. For future research, it is suggested to analyze another variabels, such as: students’ critical thinking skills and students’ logical- mathematical thinking ability.

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Section: Discussionsupporting

confidence: 87%

“…Several studies related to the heutagogy approach on learning process have been conducted by are considered effective in independent learning of students including research conducted by (Anand et al, 2021;Jazeel, 2016). However, both of these research examined the heutagogy approach on Science field.…”

Section: Introductionmentioning

confidence: 99%

E-Module of Mathematics Economic Using Heutagogy Approach for Distance Learning: Is It Effective?

et al. 2022

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“…Great interest is the capital to achieve learning goals (Deng et al, 2016). To achieve learning objectives, every teacher must understand and think about learning strategies applied during class learning (Anand et al, 2021;Biwer et al, 2020). Learning strategy is one of the important elements to be understood by the teacher.…”

Section: Discussionmentioning

confidence: 99%

Learning Video: Efforts to Improve the Quality of Natural Resource Learning for Elementary School Students

Kusumawati

Jayanta

Sukmana

2021

International j.of Elementary Education

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The low student learning outcomes are caused by the lack of learning media that can motivate students to learn. Therefore, it is necessary to develop learning media that can increase student learning motivation. This study aims to produce products in the form of learning video media on science content, especially natural resource materials. This research is a Research & Development research based on the Borg & Gall model. The subject in this research is learning video media, with the validity of the media as the object of research. This study involved one learning material expert, one instructional media expert, one instructional design expert, and field test preparation (one teacher and six students). The data collection method used questionnaires and questionnaires which were then analyzed using quantitative descriptive analysis. The results of this study indicate that from the aspect of learning materials, aspects of learning media, and aspects of learning design, the qualifications are very good with a percentage of 96.1%. From the aspect of field testing, this media preparation has very good qualifications with a percentage of 97.4%. It was concluded that the learning video media developed was suitable for use in science content, especially natural resource materials in grade IV SD. Therefore, it is recommended to use video media as an alternative in improving the quality of learning natural resource materials in the fourth grade of elementary school.

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“…Daily Standup Meetings [10,28] Sprint Planning [10,3,23,11] Brainstorming [23,22,9] Checklist [22] Weekly Sprint Meetings [16] Increment [17] Prototype [17] Product backlog refinement meeting [17,28,4] Weekly risk meeting [17] Technical specification [17] Risk Identification Meetings [23] Sprint backlog [28] Sprint review [14,3,4,18] Sprint Retrospective [3]…”

Section: Practices Referencesmentioning

confidence: 99%

“…To avoid project failure due to risk traversal, it is necessary to capture and manage risks earlier in the software development process [10]. Recognizing and acknowledging the risks of a project is not always free of complications [11,12].…”

Section: Introductionmentioning

confidence: 99%

Multi-Head CNN-based Software Development Risk Classification

Ziana M.,

2023

Int. j. electr. comput. eng. syst. (Online)

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Agile methodology for software development has been in vogue for a few decades, notably among small and medium enterprises. The omission of an explicit risk identification approach turns a blind eye to a range of perilous risks, thus dumping the management into strenuous situations and precipitating dreadful issues at the crucial stages of the project. To overcome this drawback a novel Agile Software Risk Identification using Deep learning (ASRI-DL) approach has been proposed that uses a deep learning technique along with the closed fishbowl strategy, thus assisting the team in finding the risks by molding them to think from diverse perspectives, enhancing wider areas of risk coverage. The proposed technique uses a multi-head Convolutional Neural Network (Multihead-CNN) method for classifying the risk into 11 classes such as over-doing, under-doing, mistakes, concept risks, changes, differences, difficulties, dependency, conflicts, issues, and challenges in terms of producing a higher number of risks concerning score, criticality, and uniqueness of the risk ideas. The descriptive statistics further demonstrate that the participation and risk coverage of the individuals in the proposed methodology exceeded the other two as a result of applying the closed fishbowl strategy and making use of the risk identification aid. The proposed method has been compared with existing techniques such as Support Vector Machine (SVM), Multi-Layer Perceptron (MLP), Generalized Linear Models (GLM), and CNN using specific parameters such as accuracy, specificity, and sensitivity. Experimental findings show that the proposed ASRI-DL technique achieves a classification accuracy of 99.16% with a small error rate with 50 training epochs respectively.

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A heutagogical interactive tutorial involving Fishbowl with Fish Battle and Round Robin Brainstorming: A novel syndicate metacognitive learning strategy

Cited by 5 publications

References 10 publications

E-Module of Mathematics Economic Using Heutagogy Approach for Distance Learning: Is It Effective?

E-Module of Mathematics Economic Using Heutagogy Approach for Distance Learning: Is It Effective?

Learning Video: Efforts to Improve the Quality of Natural Resource Learning for Elementary School Students

Multi-Head CNN-based Software Development Risk Classification

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