scholarly journals A Strategy Based on Genetic Algorithms for Forming Optimal Collaborative Learning Groups: An Empirical Study

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 463
Author(s):  
Oscar Revelo Sánchez ◽  
César A. Collazos ◽  
Miguel A. Redondo
Keyword(s):  
Collaborative Learning ◽  
Personality Traits ◽  
Group Formation ◽  
Point Of View ◽  
Collaborative Activity ◽  
Computational Point ◽  
Learning Groups ◽  
Learning Scenarios ◽  
Genetic Algorithm Approach ◽  
Heterogeneous Formation

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.

GroupAL: ein Algorithmus zur Formation und Qualitätsbewertung von Lerngruppen in E-Learning-Szenarien / GroupAL: an algorithm for group formation and quality evaluation of learning groups in e-learning scenarios

i-com ◽  
2014 ◽  
Vol 13 (1) ◽  
pp. 70-81 ◽  
Author(s):  
Johannes Konert ◽  
Dmitrij Burlak ◽  
Stefan Göbel ◽  
Ralf Steinmetz
Keyword(s):  
Quality Evaluation ◽  
Group Formation ◽  
Learning Groups ◽  
E Learning ◽  
Learning Scenarios ◽  
Evaluation Of Learning

Zusammenfassung Der Wissensaustausch Lernender untereinander ist für E-Learning-Systeme und computer-gestütztes Lernen generell ein wichtiger Baustein zur Förderung der Motivation, der Lernzielerreichung sowie der Verbesserung der Problemlösekompetenz. Die positiven Effekte dieses Austausches hängen jedoch stark von der Eignung der Lernpartner in einer gebildeten Lerngruppe ab. In diesem Artikel werden Kriterienkategorien vorgestellt, die ein Gruppenformationsalgorithmus für Lerngruppen berücksichtigen sollte, sowie die existierenden algorithmischen Lösungen verwandter Arbeiten. Für die gleichzeitige Berücksichtigung aller dieser Kriterien wird der Algorithmus GroupAL vorgestellt. Dieser erlaubt beispielsweise die Verwendung mehrdimensionaler Kriterien, die wahlweise homogen oder heterogen ausgeprägt sein sollen, sowie die Bildung einheitlich guter Gruppen einer gesamten Kohorte von Lernenden. Die GroupAL-Architektur ermöglicht die Verwendung verschiedener Algorithmen zur Gruppenformation und definiert ein normiertes Gütemaß für Lerngruppen, welches den Vergleich verschiedener Gruppenformationen über Kriterienvariationen und Kohortenänderungen hinweg erlaubt. Die abschließend dargestellte Evaluation zeigt, dass GroupAL unter den gewählten Bedingungen bessere Ergebnisse liefert als bisherige Ansätze und umfassendere Anwendungsmöglichkeiten zur Lerngruppenbildung bietet.

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
Keyword(s):  
Collaborative Learning ◽  
Personality Traits ◽  
Group Work ◽  
Current Knowledge ◽  
Group Structure ◽  
Group Formation ◽  
Learning Theories ◽  
Average Percentage ◽  
Context Learning ◽  
New Learning

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.

scholarly journals Cooperative Learning: Adaptive Group Formation for Collaborative Learning

2020 ◽  
Vol 9 (3) ◽  
pp. 752-754
Keyword(s):  
Collaborative Learning ◽  
Cooperative Learning ◽  
Learning Styles ◽  
Social Networking ◽  
Personality Traits ◽  
Clustering Algorithm ◽  
Group Formation ◽  
Social Networking Site ◽  
Interaction Patterns ◽  
Grouping Students

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.

Who is the Perfect Match?

i-com ◽  
2018 ◽  
Vol 17 (1) ◽  
pp. 65-77 ◽  
Author(s):  
Henrik Bellhäuser ◽  
Johannes Konert ◽  
Adrienne Müller ◽  
René Röpke
Keyword(s):  
Personality Traits ◽  
Group Formation ◽  
Perfect Match ◽  
Learning Gain ◽  
Learning Groups ◽  
Learning Group ◽  
Time Investment ◽  
The Status ◽  
And Performance ◽  
Algorithmic Approaches

Abstract Using digital tools for teaching allows to unburden teachers from organizational load and even provides qualitative improvements that are not achieved in traditional teaching. Algorithmically supported learning group formation aims at optimizing group composition so that each learner can achieve his or her maximum learning gain and learning groups stay stable and productive. Selecting and weighting relevant criteria for learning group formation is an interdisciplinary challenge. This contribution presents the status quo of algorithmic approaches and respective criteria for learning group formation. Based on this theoretical foundation, we describe an empirical study that investigated the influence of distributing two personality traits (conscientiousness and extraversion) either homogeneously or heterogeneously on subjective and objective measures of productivity, time investment, satisfaction, and performance. Results are compared to an earlier study that also included motivation and prior knowledge as criteria. We find both personality traits to enhance group satisfaction and performance when distributed heterogeneously.

COMBINATORIAL POLYNOMIALLY COMPUTABLE CHARACTERISTICS OF SUBSTITUTIONS AND THEIR PROPERTIES

2020 ◽  
Vol 7 (2) ◽  
pp. 34-41
Author(s):  
VLADIMIR NIKONOV ◽  
◽  
ANTON ZOBOV ◽  
Keyword(s):  
Mathematical Expectation ◽  
Point Of View ◽  
Small Range ◽  
Computational Point ◽  
Wide Range ◽  
Bijective Function ◽  
The Difference ◽  
Element Base ◽  
Selection Of

The construction and selection of a suitable bijective function, that is, substitution, is now becoming an important applied task, particularly for building block encryption systems. Many articles have suggested using different approaches to determining the quality of substitution, but most of them are highly computationally complex. The solution of this problem will significantly expand the range of methods for constructing and analyzing scheme in information protection systems. The purpose of research is to find easily measurable characteristics of substitutions, allowing to evaluate their quality, and also measures of the proximity of a particular substitutions to a random one, or its distance from it. For this purpose, several characteristics were proposed in this work: difference and polynomial, and their mathematical expectation was found, as well as variance for the difference characteristic. This allows us to make a conclusion about its quality by comparing the result of calculating the characteristic for a particular substitution with the calculated mathematical expectation. From a computational point of view, the thesises of the article are of exceptional interest due to the simplicity of the algorithm for quantifying the quality of bijective function substitutions. By its nature, the operation of calculating the difference characteristic carries out a simple summation of integer terms in a fixed and small range. Such an operation, both in the modern and in the prospective element base, is embedded in the logic of a wide range of functional elements, especially when implementing computational actions in the optical range, or on other carriers related to the field of nanotechnology.

Formacja prawnika wyzwaniem czasów

2017 ◽  
Vol 15 (2) ◽  
pp. 267-286
Author(s):  
Stanisław Leszek Stadniczeńko
Keyword(s):  
Higher Education ◽  
Human Capital ◽  
Young People ◽  
Personality Traits ◽  
Point Of View ◽  
Job Market ◽  
Social Lives ◽  
New Vision ◽  
Political Disputes

The author considers the questions relating to the formation of lawyers’ professional traits from the point of view of the significance which human capital and investment in this capital hold in contemporary times. It follows from the analyses, which were carried out, that the dire need for taking up actions with the aim to shape lawyers appears one of the most vital tasks. This requires taking into account visible trends in the changing job market. Another aspect results from the need for multilevel qualifications and conditions behind lawyers’ actions and their decisions. Thus, colleges of higher education which educate prospective lawyers, as well as lawyers’ corporations, are confronted by challenges of forming, in young people, features that are indispensable for them to be valuable lawyers and not only executors of simple activities. The author points to the fact that lawyers need shaping because, among others, during their whole social lives and realization of professional tasks their personality traits and potential related to communication will constantly manifest through accepting and following or rejecting and opposing values, principles, reflexions, empathy, sensitivity, the farthest-fetched imagination, objectivism, cooperation, dialogue, distancing themselves from political disputes, etc. Students of the art of law should be characterized by a changed mentality, new vision of law – service to man, and realization of standards of law, as well as perception of the importance of knowledge, skills, attitudes and competences.

scholarly journals The Impact of Game-Based, Modeling, and Collaborative Learning Methods on the Achievements, Motivations, and Visual Mathematical Literacy Perceptions

SAGE Open ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 215824402110035
Author(s):  
Aziz İlhan
Keyword(s):  
Collaborative Learning ◽  
Control Group ◽  
Conventional Instruction ◽  
Game Based Learning ◽  
Mathematical Literacy ◽  
Learning Methods ◽  
Learning Groups ◽  
The Mean ◽  
The Impact ◽  
Experimental Group

The present study aimed to investigate the effects of geometry instruction activities conducted in nature based on modeling, game-based, and cooperative learning methods on achievement, mathematical motivation, and visual mathematical literacy perceptions of third-grade elementary school students. The present study is a quantitative study conducted with a pre-test/post-test experimental design with a control group. The study was conducted with 61 students (35 students in the experimental group and 26 students in the control group). Modeling-, game-, and collaborative learning-based activities were conducted with the students in the experimental group. It was determined that the achievements of students who were instructed with modeling-based activities in geometry were high when compared to that of the students instructed with collaborative learning- and game-based methods, and those in the control group where no intervention was applied. This group was followed by the game-based and collaborative learning groups. Based on the variable of motivation, the mean motivation of the students in the modeling group was higher when compared to that of the students in the collaborative learning, game-based, and conventional instruction groups. This group was followed by the collaborative and game-based learning groups. Also, based on the visual mathematical literacy perception variable, the mean visual mathematics literacy perception of the students in the collaborative learning group was higher when compared to that of the students in the groups where the modeling, game-based, and conventional instruction methods were used. This group was followed by the modeling and game-based learning groups.

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