InRES: a digital solution for enhancing research originality and supervision in higher education

This study introduces the Innovative Research Electronic System (InRES), a digital repository developed to address research topic redundancy and supervision inefficiency in UiTM Pahang's MGT651 course. A quantitative TAM-based study involving 40 students revealed high system acceptance (overall mean = 4.02/5, 74.1% favourable ratings). Perceived Usefulness (PU) emerged as the strongest predictor of Behavioural Intention (β = 0.48, *p* < .001), particularly for enhancing topic originality (rated 4.25/5). Supervisor Impact significantly influenced adoption (β = 0.18; *r* = 0.71 with PU), and students with prior research experience reported 65% higher adoption intention than novices. User feedback prioritized feature enhancements: workflow tools like research timeline trackers (17.5% of suggestions), industry-academia collaboration (12%), and AI-driven topic matching (7.5%). Findings demonstrate that InRES success follows the formula: Adoption = 0.48(PU) + 0.39(Attitude) + 0.18(Supervisor Support), validating its potential to foster originality through accessible research management. Future development should integrate productivity automation and scalability features.

Publication Details

Journal
UiTM Institutional Repositories (Universiti Teknologi MARA)
Published
2025-09-01
Primary Topic
Meta-analysis and systematic reviews
Type
article
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article

InRES: a digital solution for enhancing research originality and supervision in higher education

UiTM Institutional Repositories (Universiti Teknologi MARA)
Meta-analysis and systematic reviews
article

InRES: a digital solution for enhancing research originality and supervision in higher education

article en

Abstract

This study introduces the Innovative Research Electronic System (InRES), a digital repository developed to address research topic redundancy and supervision inefficiency in UiTM Pahang's MGT651 course. A quantitative TAM-based study involving 40 students revealed high system acceptance (overall mean = 4.02/5, 74.1% favourable ratings). Perceived Usefulness (PU) emerged as the strongest predictor of Behavioural Intention (β = 0.48, *p* < .001), particularly for enhancing topic originality (rated 4.25/5). Supervisor Impact significantly influenced adoption (β = 0.18; *r* = 0.71 with PU), and students with prior research experience reported 65% higher adoption intention than novices. User feedback prioritized feature enhancements: workflow tools like research timeline trackers (17.5% of suggestions), industry-academia collaboration (12%), and AI-driven topic matching (7.5%). Findings demonstrate that InRES success follows the formula: Adoption = 0.48(PU) + 0.39(Attitude) + 0.18(Supervisor Support), validating its potential to foster originality through accessible research management. Future development should integrate productivity automation and scalability features.

UiTM Institutional Repositories (Universiti Teknologi MARA)
Openalex Percentile: Top 32%
Meta-analysis and systematic reviews
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