Research literacy and its predictors among university students and graduates identified by machine learning and spatial analysis

Mohammed A Mamun^{1

2

3}, Md Abu Huraira^{4

5}, Momotaj Begum^{4

6}, Md Hasibul Islam Jitu^{4

7}, Naoroj Muntashir^{4

8}, Md Maruf Khan^{4

9}, Pronab Das^{4

10}, Sadikur Rahman^{4

11}, Umme Zaida Misma^{4

12}, Sajib Nath^{4

13}, Tamim Ikram^{4

14}, Rubiya Wazed^{4

15}, Marjia Khan Trisha^{4

14}, Md Shabbir Ahamed⁴, Md Omar Faruk^{4

16}, Arpita Howlader Tisa^{4

12}, Aysha Siddiky^{4

17}, Sree Siddarth Shankar Devnath Satu^{4

18}, Abdul Kaium^{4

19}, Md Shakibul Hasan^{4

13}, Sabrina Aktar²⁰, Md Zahidul Hasan²¹, Md Mehedi Hasan^{4

22}, Mohammad Kibria^{4

23}, Tasnim B K Chowdhury^{4

14}, Milan Kumar Das^{4

18}, Md Abdulla Hell Kafi Patowary^{4

24}, Md Hamed Hasan^{4

25}, Sharmin Akter^{4

26}, Anonna Haque^{4

27}, Kulsuma Bahar Bethi^{4

28}, Jannatul Ferdaus^{4

29}, Pintu Chandra Shil^{4

30}, Md Emran Hasan^{4

31

32}, Moneerah Mohammad ALmerab³³, Firoj Al-Mamun^{4

14

34}, Nitai Roy³⁵, David Gozal³⁶

Affiliations

¹ CHINTA Research Bangladesh, Savar, 1342, Dhaka, Bangladesh. mamun@thechinta.org.
² Department of Public Health and Informatics, Jahangirnagar University, Dhaka, 1342, Bangladesh. mamun@thechinta.org.
³ Department of Public Health, University of South Asia, Dhaka, 1348, Bangladesh. mamun@thechinta.org.
⁴ CHINTA Research Bangladesh, Savar, 1342, Dhaka, Bangladesh.
⁵ Department of Public Administration, Jahangirnagar University, Dhaka, 1342, Bangladesh.
⁶ Department of Sociology, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh.
⁷ Institute of Statistical Research and Training, University of Dhaka, Dhaka, 1000, Bangladesh.
⁸ Department of Chemical Engineering, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh.
⁹ Department of Biochemistry and Molecular Biology, Primeasia University, Dhaka, 1213, Bangladesh.
¹⁰ One Health Institute, Chattogram Veterinary and Animal Sciences University, Chattogram, 4225, Bangladesh.
¹¹ Department of Philosophy, Jahangirnagar University, Dhaka, 1342, Bangladesh.
¹² Department of Public Health, Premier University, Chattogram, 4317, Bangladesh.
¹³ Department of Food Technology and Nutrition Science, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh.
¹⁴ Department of Public Health and Informatics, Jahangirnagar University, Dhaka, 1342, Bangladesh.
¹⁵ Department of Food and Nutrition, Govt. College of Applied Human Science, University of Dhaka, Dhaka, 1000, Bangladesh.
¹⁶ Saic College of Medical Science and Technology, Dhaka, 1216, Bangladesh.
¹⁷ Faculty of Nutrition and Food Science, Patuakhali Science and Technology University, Patuakhali, 8602, Bangladesh.
¹⁸ School of Science and Technology, Bangladesh Open University, Gazipur, 1705, Bangladesh.
¹⁹ Department of Acupuncture and Moxibustion & Tuina, Tianjin University of Traditional Chinese Medicine, Tianjin, 301617, China.
²⁰ Department of Library and Information Science, National University, Gazipur, 1704, Bangladesh.
²¹ Department of Chemical and Biomedical Engineering, University of Missouri, Columbia, 65211, USA.
²² Department of Anthropology, Rajshahi University, Rajshahi, 6205, Bangladesh.
²³ Department of Sociology, Shahjalal University of Science and Technology, Sylhet, 3114, Bangladesh.
²⁴ Department of Biochemistry and Molecular Biology, Jahangirnagar University, Dhaka, 1342, Bangladesh.
²⁵ Department of Biochemistry & Molecular Biology, Gopalganj Science and Technology University, Gopalganj, 8100, Bangladesh.
²⁶ Department of Food Technology and Nutritional Science, Mawlana Bhashani Science and Technology University, Tangail, 1902, Bangladesh.
²⁷ Bangabandhu Sheikh Mujib Medical College, Faridpur, 7800, Bangladesh.
²⁸ Institute of Nutrition and Food Science, University of Dhaka, Dhaka, 1000, Bangladesh.
²⁹ Department of Public Health, Hamdard University Bangladesh, Gazaria, 1510, Bangladesh.
³⁰ Department of Public Health, North South University, Dhaka, 1229, Bangladesh.
³¹ Software College, Northeastern University, Shenyang, 110169, China.
³² School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.
³³ Department of Psychology, College of Education and Human Development, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia.
³⁴ Department of Public Health, University of South Asia, Dhaka, 1348, Bangladesh.
³⁵ Department of Biochemistry and Food Analysis, Patuakhali Science and Technology University, Patuakhali, 8602, Bangladesh.
³⁶ Departments of Pediatrics, Biomedical Sciences, and Office of the Dean, Joan C. Edwards School of Medicine, Marshall University, West, VA, 25701, USA.

PMID: 41083527
PMCID: PMC12518792
DOI: 10.1038/s41598-025-19488-4

Research literacy and its predictors among university students and graduates identified by machine learning and spatial analysis

Mohammed A Mamun et al. Sci Rep. 2025.

. 2025 Oct 13;15(1):35622.

doi: 10.1038/s41598-025-19488-4.

Authors

Affiliations

¹ CHINTA Research Bangladesh, Savar, 1342, Dhaka, Bangladesh. mamun@thechinta.org.
² Department of Public Health and Informatics, Jahangirnagar University, Dhaka, 1342, Bangladesh. mamun@thechinta.org.
³ Department of Public Health, University of South Asia, Dhaka, 1348, Bangladesh. mamun@thechinta.org.
⁴ CHINTA Research Bangladesh, Savar, 1342, Dhaka, Bangladesh.
⁵ Department of Public Administration, Jahangirnagar University, Dhaka, 1342, Bangladesh.
⁶ Department of Sociology, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh.
⁷ Institute of Statistical Research and Training, University of Dhaka, Dhaka, 1000, Bangladesh.
⁸ Department of Chemical Engineering, Bangladesh University of Engineering and Technology, Dhaka, 1000, Bangladesh.
⁹ Department of Biochemistry and Molecular Biology, Primeasia University, Dhaka, 1213, Bangladesh.
¹⁰ One Health Institute, Chattogram Veterinary and Animal Sciences University, Chattogram, 4225, Bangladesh.
¹¹ Department of Philosophy, Jahangirnagar University, Dhaka, 1342, Bangladesh.
¹² Department of Public Health, Premier University, Chattogram, 4317, Bangladesh.
¹³ Department of Food Technology and Nutrition Science, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh.
¹⁴ Department of Public Health and Informatics, Jahangirnagar University, Dhaka, 1342, Bangladesh.
¹⁵ Department of Food and Nutrition, Govt. College of Applied Human Science, University of Dhaka, Dhaka, 1000, Bangladesh.
¹⁶ Saic College of Medical Science and Technology, Dhaka, 1216, Bangladesh.
¹⁷ Faculty of Nutrition and Food Science, Patuakhali Science and Technology University, Patuakhali, 8602, Bangladesh.
¹⁸ School of Science and Technology, Bangladesh Open University, Gazipur, 1705, Bangladesh.
¹⁹ Department of Acupuncture and Moxibustion & Tuina, Tianjin University of Traditional Chinese Medicine, Tianjin, 301617, China.
²⁰ Department of Library and Information Science, National University, Gazipur, 1704, Bangladesh.
²¹ Department of Chemical and Biomedical Engineering, University of Missouri, Columbia, 65211, USA.
²² Department of Anthropology, Rajshahi University, Rajshahi, 6205, Bangladesh.
²³ Department of Sociology, Shahjalal University of Science and Technology, Sylhet, 3114, Bangladesh.
²⁴ Department of Biochemistry and Molecular Biology, Jahangirnagar University, Dhaka, 1342, Bangladesh.
²⁵ Department of Biochemistry & Molecular Biology, Gopalganj Science and Technology University, Gopalganj, 8100, Bangladesh.
²⁶ Department of Food Technology and Nutritional Science, Mawlana Bhashani Science and Technology University, Tangail, 1902, Bangladesh.
²⁷ Bangabandhu Sheikh Mujib Medical College, Faridpur, 7800, Bangladesh.
²⁸ Institute of Nutrition and Food Science, University of Dhaka, Dhaka, 1000, Bangladesh.
²⁹ Department of Public Health, Hamdard University Bangladesh, Gazaria, 1510, Bangladesh.
³⁰ Department of Public Health, North South University, Dhaka, 1229, Bangladesh.
³¹ Software College, Northeastern University, Shenyang, 110169, China.
³² School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.
³³ Department of Psychology, College of Education and Human Development, Princess Nourah bint Abdulrahman University, Riyadh, 11671, Saudi Arabia.
³⁴ Department of Public Health, University of South Asia, Dhaka, 1348, Bangladesh.
³⁵ Department of Biochemistry and Food Analysis, Patuakhali Science and Technology University, Patuakhali, 8602, Bangladesh.
³⁶ Departments of Pediatrics, Biomedical Sciences, and Office of the Dean, Joan C. Edwards School of Medicine, Marshall University, West, VA, 25701, USA.

PMID: 41083527
PMCID: PMC12518792
DOI: 10.1038/s41598-025-19488-4

Abstract

The landscape of academic publishing has evolved dramatically, leading to a surge in publications and journals. The 'publish or perish' culture has resulted in undesirable practices, such as many researchers publishing in predatory journals due to institutional pressures and lack of awareness. While numerous studies have investigated knowledge of predatory journals, overall research literacy has remained underexplored. This study is the first to assess research literacy comprehensively, incorporating GIS and machine learning techniques alongside traditional statistical analyses. This study utilized a cross-sectional survey method with a questionnaire collecting information on socio-demographics, academic information, research training and experience, and research literacy. Traditional statistical analyses were performed using SPSS, while machine learning models were developed with Python and Google Colab. Supervised classification algorithms and mapping with R statistical software's 'bangladesh' package. The findings revealed that over half of the participants had poor research literacy. Significant predictors of higher research literacy included satisfaction with research courses at university education, research course taken outside university , and research-related professional engagement. Machine learning analysis identified that taking research courses outside of university was the most impactful factor for research literacy, while researchers within family members had minimal influence. The Random Forest and CatBoost models performed strongly in predicting literacy, achieving accuracy rates of 73.04% and 71.57%, respectively, and precision values of 73.29% and 71.69%, respectively, with low log loss values of 0.57 and 0.56. GIS-based spatial analyses revealed regional disparities in research literacy (χ²=9.234, p = 0.236), with certain divisions exhibiting a higher prevalence of lower literacy. This study highlights that a substantial portion of the participants lack research literacy, which is associated with multiple factors. The findings suggest the need for intervention programs to enhance research practices and awareness among students and professionals, fostering a culture of academic excellence.

Keywords: Plagiarism; Predatory journals; Research evaluation; Research literacy; Research training; Thesis students.

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Conflict of interest statement

Declarations. Competing interests: The authors declare no competing interests. Ethics approval and consent to participate: Before the study implementation, it received approval from the Institutional Review Board at Patuakhali Science and Technology University, Bangladesh [Reference Number: PSTU/IEC/2023/81]. Besides, the study adhered to the principles outlined in the revised Helsinki Declaration of 2013, ensuring ethical standards for human subject participation were met. Participants were informed about the purpose and objectives of the study through a brief description at the beginning of the questionnaire, where their written informed consent was sought for participation. They were assured of their right to withdraw from the study at any time without any obligation. It is important to note that no monetary or non-monetary remuneration or benefits were offered for participation in the study. Informed consent: Participants were informed about the purpose and objectives of the study through a brief description at the beginning of the questionnaire, where their written informed consent was sought for participation.

Figures

**Fig. 1**
Relative impact of individual features on research literacy predictions, ranked by SHAP values from the XGBoost model. *SHAP (Shapley Additive Explanations)* values represent each feature’s contribution to model output, with higher absolute SHAP values indicating greater influence on predicting research literacy category. XGBoost: Extreme Gradient Boosting. Feature value is color-coded (red: high value, blue: low value).

**Fig. 2**
Distribution of research literacy item familiarity among participants. *DOAJ*: Directory of Open Access Journals. “Not familiar at all” = 0, “Slightly familiar” = 1, “Moderately familiar” = 2, “Very familiar” = 3. Percentages reflect self-reported familiarity with each concept. Higher percentages in “Not familiar at all” and “Slightly familiar” indicate knowledge gaps. Items correspond to the ten research literacy domains assessed in the study.

**Fig. 3**
Geographic distribution of low research literacy among participants by division and thesis status in Bangladesh. Panel A (left) displays the percentage of students/graduates with low research literacy in each of the eight divisions. Panels B and C (right) show the percentages stratified by thesis group and non-thesis group, respectively. Percentages are color-coded (darker shades indicate higher proportions of low research literacy). Maps were created using the R ‘bangladesh’ package, based on self-reported division of residence. Thesis group: completed or ongoing thesis. Non-thesis group: undecided, unwilling, or no opportunity for thesis.

**Fig. 4**
Receiver Operating Characteristic (ROC) curves for machine learning models predicting research literacy status. Curves represent the classification performance of K-Nearest Neighbor (KNN), Random Forest (RF), Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), and Categorical Boosting (CatBoost) algorithms. The Area Under the Curve (AUC) values for each model are provided in the legend. Higher AUC indicates better model discrimination between high and low research literacy.

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References

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Research literacy and its predictors among university students and graduates identified by machine learning and spatial analysis

Affiliations

Research literacy and its predictors among university students and graduates identified by machine learning and spatial analysis

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

MeSH terms

LinkOut - more resources

Full Text Sources