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Inferring Vocational Interests through an AI-based Chatbot: Examining Psychometric Properties of Machine-inferred Vocational Interests Scores
No full textArtificial intelligence (AI) and Machine Learning (ML) have been hot topics recently and have been applied in various areas of psychological research. Increasing attention has been focused on using AI/ML to predict the human mind, especially personality (e.g., Hickman et al., 2021; Youyou et al., 2015). This new approach has generally been referred to as AI-based psychological assessment (Fan et al., 2023). The research results showed some promises of this new approach in measuring individual differences (Azucar et al., 2018; Settanni et al., 2018). However, other than personality, this new approach has seldom been applied to the measurement of other types of individual differences such as career interests, emotional intelligence, cognitive ability, etc. The present research focuses on vocational interests, which reflect relatively stable individual differences in motives, goals, and personal strivings both within and beyond the vocational domain (Stoll et al., 2017; Van Iddekinge et al., 2011). Vocational interests hold a crucial position in applied psychology in that they are important noncognitive factors that influence major work and life outcomes, and their assessment deserves innovation (Chernyshenko et al., 2011). In the current research, I explore the feasibility of using an AI-based chatbot to measure vocational interests. Specifically, I build predictive models using text scripts to predict vocational interests and then comprehensively examine the psychometric properties of machine-inferred interests scores: reliability, internal structure, convergent and discriminant validity, and criterion-related validity
Understanding The Effectiveness of Teaching For Artistic Behavior (TAB) In Arts Education: A Case Study
Get PDFArt education longs to prove its efficiency and effectiveness in providing essential lifelong skills to young students in schools. The purpose of this qualitative case study is to show the benefits and variations of a different teaching method, Teaching for Artistic Behavior (TAB), compared to other methods that many educators use. Data will be collected from teachers in art classrooms who use the method of TAB and incorporate the Studio Habits of Mind, through interview surveys and student artifacts. This study will impact arts educators by providing information regarding a different and perhaps beneficial way to deliver holistic and effective curricula to students
Developing Anti-Racist Teaching Practices to Represent a Diverse Student Population
Get PDFThe issue that this case study will address is the need for an anti-racist high school art curriculum. In order to better represent today’s diverse society, educators need to incorporate anti-racist teaching practices both within their curriculum and their classroom environments. I will examine how systemic racism as a society has led to lack of diversity within the field of art education and identify what anti-racist pedagogical practices can be put into place to combat it
