Development and Validation of Academic Dishonesty Scale (ADS): Presenting a Multidimensional Scale

Bashir, Hilal; Bala, Ranjan

doi:10.12973/iji.2018.1125a

Cited by 43 publications

(41 citation statements)

References 57 publications

(65 reference statements)

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“…At the level of dishonest behavior recognition, in the early days, researchers mostly used students' self-reporting methods for research. For example, Bashir et al (2018) developed a scale that is suitable for detecting various types of learning dishonesty [17]. Peer et al (2014) have found that students' reluctance to admit cheating means that self-reporting often underestimates academic dishonesty [18].…”

Section: Rq3: What Are the Methods To Identify College Students' Learmentioning

confidence: 99%

Online Academic Dishonesty of College Students: A Review

Chen¹,

Long²,

Liu³

et al. 2020

Proceedings of the 2020 International Conference on Advanced Education, Management and Social Science (AEMSS2020)

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e-Learning provides students with an open, free, and self-supervised scene, which has found a feasible path for lifelong education. The quality of online learning and the certification of achievements must be based on the real learning process. According to the existing literature, research on online academic dishonesty (OAD) is relatively rare. We need to advance future research based on the past experience on online academic dishonesty, and we also need to systematically sort out the research conclusions and possible development directions of this topic. In this paper, the author systematically combed the relevant literature on online academic dishonesty, covering most of the relevant papers as of the end of 2019. Most research on online academic fraud has the following characteristics: using questionnaires to obtain exploration conclusions, focusing on learners in a certain discipline or situation, lack of research on big data learning behavior sample data, and the formation mechanism of online academic dishonesty behavior needs to be further studied and elaboration. The research results show that online academic dishonesty is indeed widespread, and the factors that cause the dishonesty behavior come from many aspects such as personality, cognition, teaching, system, etc. In future research, it is necessary to identify online academic dishonesty in time and take comprehensive intervention measures to make integrity and moral culture in online environments.

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Section: Rq3: What Are the Methods To Identify College Students' Learmentioning

confidence: 99%

Online Academic Dishonesty of College Students: A Review

Chen¹,

Long²,

Liu³

et al. 2020

Proceedings of the 2020 International Conference on Advanced Education, Management and Social Science (AEMSS2020)

View full text Add to dashboard Cite

show abstract

“…Logical validation was carried out by several experts related to the field then the validation results were analyzed using V-Aiken. Logical validation was analyzed using product moment correlation (Bashir & Bala, 2018;Sadhu & Laksono, 2018). Data obtained from the results of the study were then subjected to the analysis prerequisite test, namely the normality and homogeneity tests (Aiken, 1985;Mardapi, 2008).…”

Section: Methodsmentioning

confidence: 99%

Escalation in Students’ Science Process Skills on Chapter Wave Vibration and Sound Through Guided Inquiry Learning Model

Winarti

Sari

2020

JOTALP

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This study aims to determine: (1) the effect of guided inquiry models on students' science process skills, (2) improvement of skills the science process of students with learning inquiry models, This research is a quasi-experimental study with non-equivalent control group design. Data collection techniques used were test and non-test. The instruments in this study were a pretest-posttest cognitive ability test sheet, student worksheets and an observation sheet for science process skills. The data analysis technique used is non-parametric statistics with the Mann Whitney U test, Normalized Gain (N-Gain) and descriptive analysis. The results of this study are that (1) Physics learning using guided inquiry learning models influences the cognitive abilities of students with a significance level (sig. 2-tailed) of 0.013. (2) Physics learning using guided inquiry learning models can improve students' cognitive abilities with an average value of n-gain of 0.701 which is included in the high criteria. Keywords: Guided Inquiry, Science Process Skills, Cognitive Skills, Wave Vibration and Sound.

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“…Three forms of academic dishonesty in general, namely (1) giving, speaking and receiving information, (2) using prohibited materials, (3) utilizing people's weaknesses, procedures or processes to gain academic benefits [25]. Bashir and Bala who developed an instrument of academic dishonesty scale suggested that the characteristics of academic dishonesty were cheating / cheating during exams, plagiarism, asking for help from others, working with friends to cheat, falsify and lie in complementing assignments [26].…”

Section: Forms Of Academic Dishonestymentioning

confidence: 99%

“…The instrument for measuring dishonesty was adapted from Hilal Bashir and Ranjan Bala who developed the Academic Dishonesty Scale (ADS) measurement tool. The ADS instrument has a high internal consistency value α = 0.831 [26]. The ADS instrument was translated to Indonesian for ease of getting response.…”

Section: Instrumentationmentioning

confidence: 99%