Ali, Hazhmat
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The Association Between Irregular Sleep Patterns and Learning Outcomes: Implications for Students’ Health in Iraq Ali, Hazhmat; Musa, Dildar Haji; Mohammed, Ary Habeeb; Abdulraheem, Hiwa; Salahadeen, Sherzad; Mustafa, Alind
Makara Journal of Health Research Vol. 29, No. 2
Publisher : UI Scholars Hub

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Abstract

Background: Students often exhibit irregular sleep patterns due to rigorous academic workloads, which exert a considerable negative impact on their mental health. The present study aims to investigate the influence of irregular sleep on academic performance. Methods: This study recruited a cohort of 409 medical students of both genders. Upon their consent, participants filled out a closed-ended questionnaire on various sleep parameters, including sleep habits, duration, and environment. Results: Students with irregular sleep patterns reported higher rates of sleep deprivation, late sleep onset, and troubled sleep. Moreover, they spent a longer duration using smart devices before bedtime and experienced higher levels of stress. Irregular sleep demonstrated a positive correlation with sleep deprivation, sleep duration, troubled sleep, and the duration of smart device use (p = 0.000), energy drink consumption (p = 0.040), and junk-food intake (p = 0.000). Students exhibited poor academic performance, frequently experienced fatigue, and were unfocused. Irregular sleep was positively correlated with overall academic performance (p = 0.002), fatigue, and focus in class (p = 0.000). Conclusion: The findings indicate a significant impact of irregular sleep on learning outcomes and mental health among medical students. Thus, effective strategies are critically required to enhance sleep within this population.
Prevalence and Perceived Academic Impacts of Artificial Intelligence Tool Use among Medical Students Ali, Hazhmat; Alhakim, Maryam; Mohammed, Heleen; Yousif, Aram; Sabri, Laween; Ahmed, Jehat
Journal of Applied Artificial Intelligence in Education Vol 2, No 2 (2027): January 2027
Publisher : Academic Bright Collaboration

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66053/jaaie.v2i2.389

Abstract

Artificial intelligence (AI) is increasingly transforming medical education by supporting personalized and efficient learning, yet its growing use among medical students raises concerns about academic integrity, data privacy, ethical practice, and potential overdependence, making it necessary to examine its prevalence, usage patterns, perceived benefits and limitations, and association with self-reported academic outcomes. A cross-sectional single-institutional study employing convenience sampling was conducted at the University of Duhok, Kurdistan Region of Iraq. Participants completed a closed-ended questionnaire that gathered data on demographics, prevalence, and patterns of AI use, and perceived advantages and limitations. Data analysis was performed using SPSS version 26.A majority of students (61%) reported regular use of AI tools. ChatGPT was the most frequently utilized tool (66.3%), primarily for summarizing materials and completing writing tasks. Most participants perceived AI as beneficial for writing, academic performance, and time management; however, only one-third considered AI-generated content reliable. Reported disadvantages included diminished critical thinking, increased passive learning, decreased reliance on traditional resources, ethical concerns, and ambiguous institutional policies. AI use was primarily associated with self-reported improvements in writing, time efficiency, and academic performance, but also with reduced critical thinking. Regular users were more likely to report improvements in writing, time management, and academic achievement, as well as a greater decline in critical thinking. No significant association was found between AI use and increased study motivation. Although this study was conducted at a single institution, the findings indicate that while AI is perceived to enhance learning and academic performance, its use should be balanced with strategies that foster critical thinking and independent learning. Institutions are encouraged to develop clear guidelines and provide training to support the ethical and effective integration of AI in educational contexts.