scholarly journals The Use of Personality Traits to Enhance Theory-driven Group Formation

2020 ◽  
Vol 28 ◽  
pp. 796-818
Author(s):  
Rachel Carlos Duque Reis ◽  
Kamila Takayama Lyra ◽  
Clausius Duque Gonçalves Reis ◽  
Bruno Elias Penteado ◽  
Seiji Isotani

Group formation is an important and challenging element for designing successful CSCL scenarios. Despite efforts from the scientific community in developing more effective algorithms to support group formation processes, we still face problems related to learners’ resistance and demotivation towards group work. In this sense, diverse studies highlight the importance of considering learners’ personality traits to form groups, since this factor can influence students’ performance and induce diverse actions and behaviors in group work. Therefore, this paper presents G-FusionPT (Group Formation USIng Ontology and Personality Trait), a group formation algorithm that support new learning roles, denominated Affective Collaborative Learning roles, based on relation between collaborative learning theories and students’ personality traits. The algorithm is based on a collaborative ontology to understand the learning theories (e.g., context, learning activities, group structure), and learners profile to understand learners’ needs (e.g., target/current knowledge/skill). To evaluate the algorithm, we used a 300 student simulated sample wit varying group size (three, five, and seven members), and compared G-FusionPT results to other group formation algorithms: G-Fusion (based specifically on collaborative learning theories) and Random (no strategy or criterion). The results demonstrated the effectiveness of G-FusionPT against G-Fusion and Random algorithms, as it generated the highest average percentage of learners in well-formed groups and lowest averagepercentage of learners in unfit groups.

Author(s):  
Changhao Liang ◽  
Rwitajit Majumdar ◽  
Hiroaki Ogata

AbstractCollaborative learning in the form of group work is becoming increasingly significant in education since interpersonal skills count in modern society. However, teachers often get overwhelmed by the logistics involved in conducting any group work. Valid support for executing and managing such activities in a timely and informed manner becomes imperative. This research introduces an intelligent system focusing on group formation which consists of a parameter setting module and the group member visualization panel where the results of the created group are shown to the user and can be graded. The system supports teachers by applying algorithms to actual learning log data thereby simplifying the group formation process and saving time for them. A pilot study in a primary school mathematics class proved to have a positive effect on students’ engagement and affections while participating in group activities based on the system-generated groups, thus providing empirical evidence to the practice of Computer-Supported Collaborative Learning (CSCL) systems.


Collaborative learning affects with lot of factors like student’s personality, their interaction patterns, learning styles etc. Grouping of students is one of the important factors. It is important to arrange groups by skills and/or backgrounds. Hence it is noteworthy to create groups based on specific skills of students. Generally the students can be randomly grouped or grouped themselves. But this method of grouping students based on certain features like personality traits can improve the efficiency of collaborative learning. The student’s data can be collected from social networking site like Facebook. The personality of each student can be identified by comparing the individual’s chat history with psycholinguistic databases. The main objectives of this paper are to identify the student’s personality. Based on that, the group of students can be formed using k-means clustering algorithm.


Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 463
Author(s):  
Oscar Revelo Sánchez ◽  
César A. Collazos ◽  
Miguel A. Redondo

Considering that group formation is key when developing activities in collaborative learning scenarios, this paper aims to propose a strategy based on a genetic algorithm approach for achieving optimal collaborative learning groups, considering the students’ personality traits as grouping criteria. A controlled experiment was designed with 238 students, quantifying their personality traits through the “big five inventory” (BFI), forming working groups and developing a collaborative activity in programming and related courses. The experiment results allowed validation, not only from a computational point of view evaluating the algorithm performance but also from a pedagogical point of view, confronting the results obtained by students applying the proposed approach with those obtained through other group formation strategies. The highlight of the study is that those groups whose formation was pre-established by the teachers through the proposed strategy have generally had a better collaborative performance than the groups with traditional formation, except in the case of heterogeneous formation, at the time of developing a collaborative activity. In addition, through the experiment, it was found that not considering criteria related to personality traits before the group formation generally led to lower results.


2021 ◽  
Author(s):  
Geiser Chalco Challco

Main protocol in portugues used to conduct a quasi-experimental study of group formation of high performance in Collaborative-Learning-Projects with Agile Methods


2016 ◽  
Vol 17 (2) ◽  
pp. 283-295 ◽  
Author(s):  
Yael Feldman-Maggor ◽  
Amira Rom ◽  
Inbal Tuvi-Arad

This study examines chemistry lecturers' considerations for using open educational resources (OER) in their teaching. Recent technological developments provide innovative approaches for teaching chemistry and visualizing chemical phenomena. End users' improved ability to upload information online enables integration of various pedagogical models and learning theories. These improvements strengthen the need for up-to-date evaluation tools for educational websites. Building on existing taxonomies, a set of new criteria for the evaluation of online learning materials was developed and used to analyze 100 websites directed towards teaching chemistry. In addition, a questionnaire was circulated among 100 chemistry lecturers from various higher education institutions in Israel, 66 of whom responded. Subsequently, interviews were conducted with 17 of the questionnaire respondents. Our findings demonstrate that most of the chemistry lecturers who were interviewed integrate innovative learning materials such as simulations, videos and exercises found online in their teaching, but do not use web 2.0 that enables content sharing and collaborative learning. With respect to the selection of web-based learning materials, we found that the lecturers interviewed tended to select OER intuitively, mainly considering the reliability of information, pedagogical issues and the visual contribution, while paying less attention to collaborative learning and content sharing.


2016 ◽  
Vol 1 (2) ◽  
pp. 52-61
Author(s):  
Diana Tien Irafahmi ◽  
Sulastri Sulastri

The 2013 curriculum mandates the importance of collaborative learning designed to educate students to be more productive, creative, and innovative with a high level of affective skills. Collaborative learning can be manifested in the form of a textbook. This research is aimed at developing an accounting textbook in accordance with the mandate of the 2013 curriculum. The selected model is IDI which consists of three main phases: defining, developing and evaluating. The methods chosen are interview, observation, and document review which are analyzed qualitatively. The research was conducted in 4 senior high schools in Malang. The finding shows that at defining phase, there is a need to develop an accounting textbooks using collaborative learning and corresponding to the new accounting standards, namely IFRS. Therefore, at the developmental phase, we construct a prototype book ready to be evaluated. The result of evaluation phase shows that the textbook is valid on the overall aspects including the content, the presentation, the graphic, and the language, with an average percentage of 93.7%.


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