Contract Faculty in Telangana Universities: Disparities in Recognition, Workload and Professional Development

This study investigates the disparities in recognition, benefits, teaching load, job security, and professional development opportunities experienced by contract faculty in Telangana universities. Despite their critical role in sustaining higher education, contract faculty often face systemic challenges not encountered by their tenure-track counterparts. The objective is to evaluate these inequities and propose actionable recommendations for fostering a more equitable and supportive academic environment. Using a descriptive survey design, data were collected from 211 contract faculty members across nine universities in Telangana, spanning disciplines such as Sciences, Social Sciences, Humanities & Arts, and Engineering. A semi-structured questionnaire incorporating a five-point Likert scale was administered via Google Forms. Statistical analysis was conducted using SPSS, employing descriptive statistics, one- way ANOVA, and homogeneity tests to assess disparities. Findings reveal that 100% of respondents reported receiving no Dearness Allowance, House Rent Allowance, or medical benefits. Additionally, 30.3% lacked leave benefits and only 21.8% had access to professional development opportunities. The mean score for recognition-related perceptions was 2.92 (SD=1.690), indicating low institutional acknowledgment. Teaching loads were reported as equal or higher than those of regular faculty, with 65 respondents indicating a “very high” workload. This study offers region-specific insights into the lived realities of contract faculty in Telangana, contributing to the discourse on academic equity in Indian higher education. The recommendations-enhancing recognition practices, ensuring equitable benefits, balancing workloads, improving job security and expanding professional development access- align with broader institutional reforms and aim to improve job satisfaction, retention, and the overall quality of education.

The authors declare no conflict of interest.

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The datasets used in this study are openly available at [repository link] and the source code is available on GitHub at [GitHub link].

This work did not receive any external funding.