Analyzing Peer Influence in Ethical Judgment: Collaborative Ranking in a Case-Based Scenario

Claudio Álvarez*, Gustavo Zurita, Andrés Carvallo

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Peer influence is how an individual's beliefs, actions, and choices can be influenced by the opinions and behaviors of their peers. Peer influence can affect the moral behavior of individuals. In this study, we analyze peer influence in the context of case-based learning activity in ethics education. To conduct this type of activity, we introduce EthicRankings, a groupware environment that enables students to analyze an ethical case and reason about it by ranking the actors involved according to some ethical criteria. A study with a sample of 64 engineering students was conducted at a Latin American university to analyze peer influence from a dual standpoint in an activity comprising an individual response phase followed by a collaborative phase with anonymous chat interaction. Firstly, we determine how likely a student is to change their rankings in the collaborative phase when observing their peers’ rankings and interacting with them anonymously. Secondly, we compare positive, neutral, and negative sentiment variations in students’ written justifications for rankings before and after collaborating. Results show that students are highly likely to change their responses in the collaborative phase if their responses differ significantly from their peers’ in the individual phase. Also, sentiments in written ranking justifications vary in ways consistent with changes in ranking. The pedagogical implications of these findings are discussed.

Original languageEnglish
Title of host publicationCollaboration Technologies and Social Computing - 29th International Conference, CollabTech 2023, Proceedings
EditorsHideyuki Takada, D. Moritz Marutschke, Claudio Alvarez, Tomoo Inoue, Yugo Hayashi, Davinia Hernandez-Leo
PublisherSpringer Science and Business Media Deutschland GmbH
Pages19-35
Number of pages17
ISBN (Print)9783031421402
DOIs
StatePublished - 2023
EventCollaboration Technologies and Social Computing 29th International Conference, CollabTech 2023 - Osaka, Japan
Duration: 29 Aug 20231 Sep 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14199 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceCollaboration Technologies and Social Computing 29th International Conference, CollabTech 2023
Country/TerritoryJapan
CityOsaka
Period29/08/231/09/23

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

Keywords

  • Case-Based Learning
  • Ethical Judgment
  • Groupware
  • Peer Influence

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