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Learning Community and Its Impact on Attitude toward Computer-Based Statistics
Author(s) -
Gaffar Hafiz Sagala,
Ramdhansyah Ramdhansyah,
Ulfa Nurhayani
Publication year - 2021
Publication title -
dinamika pendidikan/dinamika pendidikan
Language(s) - English
Resource type - Journals
eISSN - 2502-5074
pISSN - 1907-3720
DOI - 10.15294/dp.v16i1.27303
Subject(s) - likert scale , nonprobability sampling , group cohesiveness , mathematics education , task (project management) , statistics , psychology , computer science , social psychology , mathematics , engineering , sociology , population , demography , systems engineering
This study examined the three dimensions that should exist in a learning community, namely Student Cohesiveness, Integration, and Task Orientation, related to their influence on attitude toward computer-based statistics. Attitude toward computer-based statistics itself is measured using constructs of the revised Technology Acceptance Model (TAM). This study was designed to justify the value of information systems (IS) in overcoming accounting students' statistical problems. The use of IS probable to reduce the pressure in dealing with statistics so that there is an opportunity to increase accounting students' competitive advantage. The respondents consisted of 105 undergraduate accounting students. The data was collected using a 5-scale Likert questionnaire then analyzed using Structural Equational Modelling (SEM). With purposive sampling, this study was collected 105 responses obtained from private and state universities. The results indicate that task orientation is the key indicator of the learning community, affecting attitude toward computer-based statistics. Meanwhile, the second-order factors show that all three predictors were essential in explaining attitude toward computer-based statistics and significantly impacted Reuse Intention. This study also suggests implementing an informal learning community to build learning dynamics that are more independent but still controllable so that the learning topic is integrated with certain subjects.

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