No Anxious Student is Left Behind: Statistics Anxiety, Personality Traits, and Academic Dishonesty—Lessons from COVID-19

• Main Authors: Pnina Steinberger, Yovav Eshet, Keren Grinautsky
• Format: Article
• Language: English
• Published: MDPI AG 2021-04-01
• Series: Sustainability
• Subjects: statistics anxiety; personality traits; academic dishonest; face-to-face learning; emergency remote teaching; COVID-19
• Online Access: https://www.mdpi.com/2071-1050/13/9/4762

Scholarly studies have revealed that exposure to statistics courses affect students’ anxiety levels and that this has been associated with unethical misconduct. Thus, the present research’s main objective is to comprehend the mediating role Statistics Anxiety plays on the relationship comprising students’ personality traits and academic dishonesty as manifesting before and during the COVID-19 pandemic. Its aim is to understand this phenomenon and provide theoretical tools for fostering sustainably personalized distance learning and instruction. Data were collected from students studying for a bachelor’s degree in the social sciences at three different Israeli colleges. The sample comprises 316 participants and data were analyzed using Structural Equation Modelling (SEM). The results show a significant mediation manifested by an indirect effect between personality traits and academic dishonesty via statistics anxiety only in emergency remote teaching, although no parallel significant mediation was observed in the face-to-face course. These results could be explained by differences in delivery methods. Thus, we recommend that in the emergency remote teaching environment instructors’ presence include: (1) supportive, emphatic interaction to reduce virtual distance and (2) Social Emotional Learning (SEL) strategies, which foster students’ learning challenges and prevent anxiety and academic dishonesty.