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Detecting probable cheating during online assessments based on time delay and head pose
15 references·8 citing·42 second hop
Detecting probable cheating during online assessments based on time delay and head pose (2017)Detecting probable cheating during online…Journal of Business Ethics (2017)Journal of Business EthicsChanging Course: Ten Years of Tracking Online Education in the United States. (2013)Changing Course: Ten Years of…Surveying the extent of involvement in online academic dishonesty (e-dishonesty) related practices among university students and the rationale students provide: One university’s experience (2012)Surveying the extent of invol…Cheating in the Digital Age: Do Students Cheat More in Online Courses?. (2010)Cheating in the Digital Age: …Assessment Design and Cheating Risk in Online Instruction (2010)Assessment Design and Cheatin…Bayesian Procedures for Identifying Aberrant Response-Time Patterns in Adaptive Testing (2008)Bayesian Procedures for Ident…Are Online Exams an Invitation to Cheat? (2008)Are Online Exams an Invitatio…Exploring the types and reasons of Internet-triggered academic dishonesty among Turkish undergraduate students: Development of Internet-Triggered Academic Dishonesty Scale (ITADS) (2007)Exploring the types and reaso…Gaze aversion: A response to cognitive or social difficulty? (2005)Gaze aversion: A response to …A structural modeling investigation of the influence of demographic and attitudinal factors and in-class deterrents on cheating behavior among accounting majors (2002)A structural modeling investi…Predictors of Cheating among Early Adolescents: Academic and Social Motivations (2001)Predictors of Cheating among …Academic dishonesty and distance learning: Student and faculty views. 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References

  • 1957Techniques of Neutralization: A Theory of Delinquency5,839 cited
  • 1993Science and Engineering Indicators1,631 cited
  • 2013Changing Course: Ten Years of Tracking Online Education in the United States.1,584 cited
  • 2017Journal of Business Ethics856 cited
  • 1998Learning from the Literature on Collegiate Cheating: A Review of Empirical Research330 cited
  • 2001Predictors of Cheating among Early Adolescents: Academic and Social Motivations280 cited
  • 2005Gaze aversion: A response to cognitive or social difficulty?279 cited
  • 2010Cheating in the Digital Age: Do Students Cheat More in Online Courses?.242 cited
  • 2008Are Online Exams an Invitation to Cheat?219 cited
  • 2000Academic dishonesty and distance learning: Student and faculty views.176 cited
  • 2008Bayesian Procedures for Identifying Aberrant Response-Time Patterns in Adaptive Testing172 cited
  • 2007Exploring the types and reasons of Internet-triggered academic dishonesty among Turkish undergraduate students: Development of Internet-Triggered Academic Dishonesty Scale (ITADS)162 cited
  • 2012Surveying the extent of involvement in online academic dishonesty (e-dishonesty) related practices among university students and the rationale students provide: One university’s experience88 cited
  • 2002A structural modeling investigation of the influence of demographic and attitudinal factors and in-class deterrents on cheating behavior among accounting majors

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87 cited
  • 2010Assessment Design and Cheating Risk in Online Instruction86 cited
  • Cited by

    • 2021E-cheating Prevention Measures: Detection of Cheating at Online Examinations Using Deep Learning Approach -- A Case Study43 cited
    • 2022Facial Recognition System to Detect Student Emotions and Cheating in Distance Learning41 cited
    • 2021A secure online exams conceptual framework for South African universities41 cited
    • 2019Impact of pressure, self-efficacy, and self-competency on students’ plagiarism in higher education40 cited
    • 2022Factors associated with online examination cheating38 cited
    • 2021Ensuring Academic Integrity in Online Assessments: A Literature Review and Recommendations36 cited
    • 2020Online Academic Dishonesty of College Students: A Review25 cited
    • 2024Gaze Based Online Examination Cheat Detection with future integration of Deep Learning Models15 cited