A Media Richness Theory-Based Analysis of Students' Communication Experience in AI-Assisted Consultation

Recent advances in artificial intelligence (AI) have expanded students' consultation options beyond traditional sources such as parents, peers, and counselors. This study examines the emerging practice of AI-assisted consultation among Indonesian university students, employing Media Richness Theory (MRT) as an analytical framework to evaluate perceived media richness. A quantitative survey was administered to 553 students who had previously utilized AI for consultation purposes. Results indicate that AI is generally perceived as a “rich” medium, with an overall score of 3.78. In terms of MRT dimensions, AI scored highly in ambiguity reduction (4.02), immediacy of feedback (4.16), cue multiplicity (3.84), and message personalization (3.91). However, comparisons with conventional consultation methods (3.43) and the perceived long-term impact of AI-based interactions (3.60) were rated at a moderate level. These findings suggest that while AI demonstrates notable potential in delivering rapid, tailored, and multifaceted responses, its effectiveness remains limited when assessed against traditional human counseling, particularly regarding sustained outcomes. Consequently, AI should be positioned as a complementary tool rather than a substitute for human counselors. Enhancing AI’s capacity to produce enduring psychological and developmental support will be essential to fully leverage its role in educational and psychosocial consultation contexts.

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Publication Details

Journal
MediaTor (Jurnal Komunikasi)
Published
2025-06-30
DOI
https://doi.org/10.29313/mediator.v18i1.6816
Citations
1
Primary Topic
Attachment and Relationship Dynamics
Type
article
Field-Weighted Citation Impact
2.44
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article

A Media Richness Theory-Based Analysis of Students' Communication Experience in AI-Assisted Consultation

Mohamad-Noor Salehhuddin Sharipudin, Detta Rahmawan, Ira Mirawati
1 citations
MediaTor (Jurnal Komunikasi)
Attachment and Relationship Dynamics
2.44
article

A Media Richness Theory-Based Analysis of Students' Communication Experience in AI-Assisted Consultation

Mohamad-Noor Salehhuddin Sharipudin, Detta Rahmawan, Ira Mirawati
article en
1 citations

Abstract

Recent advances in artificial intelligence (AI) have expanded students' consultation options beyond traditional sources such as parents, peers, and counselors. This study examines the emerging practice of AI-assisted consultation among Indonesian university students, employing Media Richness Theory (MRT) as an analytical framework to evaluate perceived media richness. A quantitative survey was administered to 553 students who had previously utilized AI for consultation purposes. Results indicate that AI is generally perceived as a “rich” medium, with an overall score of 3.78. In terms of MRT dimensions, AI scored highly in ambiguity reduction (4.02), immediacy of feedback (4.16), cue multiplicity (3.84), and message personalization (3.91). However, comparisons with conventional consultation methods (3.43) and the perceived long-term impact of AI-based interactions (3.60) were rated at a moderate level. These findings suggest that while AI demonstrates notable potential in delivering rapid, tailored, and multifaceted responses, its effectiveness remains limited when assessed against traditional human counseling, particularly regarding sustained outcomes. Consequently, AI should be positioned as a complementary tool rather than a substitute for human counselors. Enhancing AI’s capacity to produce enduring psychological and developmental support will be essential to fully leverage its role in educational and psychosocial consultation contexts.

MediaTor (Jurnal Komunikasi)Vol. 18(1)
Padjadjaran University (ID)
Quality Education
Openalex Percentile: Top 11%
Attachment and Relationship Dynamics
2.44
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A Media Richness Theory-Based Analysis of Students' Communication Experience in AI-Assisted Consultation — Mohamad-Noor Salehhuddin Sharipudin, Detta Rahmawan, et al. · MediaTor (Jurnal Komunikasi) (2025) | TGRS Research Map | TGRS