arXiv subjects

Jhonathan Sora-Cardenas

Publications and source records attributed to Jhonathan Sora-Cardenas.

4 recordsLinked to original sources

arXiv2026

When Does It Become Cheating? Exploring the Roles of Self-Efficacy and the Impostor Phenomenon in Computing Students' Perceptions of Academic Dishonesty

Academic dishonesty is an urgent problem in computer science (CS) education, compounded by the rise of artificial intelligence (AI) and the prevalence of online learning in a post-COVID world. Self-efficacy and the impostor phenomenon are psychological constructs linked to academic dishonesty, yet little research has examined how they relate to how students perceive it. This study investigates the interplay between the impostor phenomenon, self-efficacy, and CS students' perceptions of academic integrity, in a context where online learning and AI agents have become commonplace. We conducted an online, asynchronous survey of undergraduate students (n = 443) in introductory to mid-level computing courses at a large Southeastern U.S. university. The survey collected measures of self-efficacy, responses to 13 potential cheating scenarios, the impostor phenomenon (Clance Impostor Phenomenon Scale), and demographic information. We observed a significant negative correlation between self-efficacy and the impostor phenomenon, and a positive correlation between the impostor phenomenon and judging an AI-related scenario as serious cheating. The impostor phenomenon was also correlated with perceived course dedication and prior teaching assistant (TA) experience, whereas self-efficacy was correlated with ethnicity. These findings highlight the need to better understand students' perceptions of AI and to keep the impostor phenomenon present in conversations about academic integrity in higher education scenarios.

cs.CY↗

arXiv2026

Exploring the Effects of Personality in Human-Agent Interactions: A Study on User-Agent Synchrony with Human-based Vocalics

User trust is paramount in human-agent interactions, as it allows users to feel comfortable being themselves around an agent. The process of building user rapport starts in how an agent was designed, from its modality to the setting, to any of the many features and characteristics that can be tailored. All these aspects can affect whether users will be able to properly interact with the virtual agent and achieve the intended purpose. One such feature that is critical in human-human interactions is personality. A person's personality can strongly influence whether those that interact with them perceive them as trustworthy. This study used virtual agents generated from human voices with known personality traits to evaluate user perceptions. We found that extraverted agents were deemed to be more likeable by users, and that there was no significant effect of user-agent synchrony on user perceptions of the agent. In addition, it was found that user personality, without regard for agent personality, affected user perceptions of the agents. Our observations suggest that user perceptions may depend more on agent-topic synchrony than user-agent synchrony, and contribute to the broader community with considerations for the design of effective human-agent interactions.

cs.HC↗

arXiv2026

Design, development, and preliminary validity and reliability evidence of the Software Engineering Self-Efficacy Scale (SESES)

The purpose of this research is to design, develop, implement, and provide preliminary validity and reliability evidence of the Software Engineering Self-Efficacy Scale (SESES). Framed by a conceptual framework using guidance in software engineering curriculum and concepts along with the notion of self-efficacy, we generated an initial item pool of n = 87 items to operationalize and measure software engineering self-efficacy among undergraduate computing students. The conceptual framework traces five dimensions: 1) Requirements Engineering, 2) Teamwork and Collaboration, 3) Software Quality Management, 4) Software Design and Architecture, and 5) Software Agile Methodologies. We pilot tested the SESES with n = 527 undergraduate computing students who had completed a software engineering course in the current semester or a previous academic semester. We employed Exploratory Factor Analysis (EFA) with the Principal Axis Factoring method and an oblique (Promax) rotation to examine the underlying structure of the SESES, resulting in the same five internally consistent latent constructs in the conceptual framework with minimal cross-loading and a simple structure in the pattern matrix, explaining approximately 57% of the variability in these data. Our findings suggest that software engineering self-efficacy is a multidimensional construct of five theorized and correlated, yet distinct latent factors. We unpack the limitations and delimitations of the research while exploring undergraduate computing students' software engineering self-efficacy using necessary domain-specific measurements.

cs.SE↗

arXiv2026

Exploring the Interplay Between Voice, Personality, and Gender in Human-Agent Interactions

To foster effective human-agent interactions, designers must understand how vocal cues influence the perception of agent personality and the role of user-agent alignment in shaping these perceptions. In this work, we examine whether users can perceive extroversion in voice-only artificial agents and how perceived personality relates to user-agent synchrony. We conducted a study with 388 participants, who evaluated four synthetic voices derived from human recordings, varying by gender (male, female) and personality expression (introverted, extroverted). Our results show that participants were able to differentiate perceived extroversion in female agent voices, but not consistently in male voices. We also observed evidence of perceived personality synchrony, particularly in participants' evaluations of the first agent encountered, with this effect more pronounced among male participants and toward male agents. We discuss these findings in light of limitations in stimulus diversity and voice representation, and outline implications for the design of voice-based agents, particularly regarding the interaction between gender, personality perception, and initial user impressions. This paper contributes findings and insights to consider the interplay of user-agent personality and gender synchrony in the design of human-agent interactions.

cs.HC↗