Matt Bernacki, Ph.D.

Program Coordinator, Learning Sciences and Psychological Studies

Area Chair, Learning, Development, and Psychological Sciences

Associate Professor

Journal Article

Ren, S., Greene, J., Bernacki, M., & Ding, L. (2026). Beyond the black box: The resource-intervention match framework for explaining differential effects of self-regulated learning interventions. Learning and Individual Differences, 125, 102843.

Fabian, A., Stein, X., Berens, F., Tsarava, K., Wagner, W., von Keyserlingk, L., Golle, J., Greene, J., Bernacki, M., Paravicini, W., & others. (2026). Investigating motivational fluctuation and dropout among talented primary school children in a self-paced online mathematics course. ZDM–Mathematics Education, 1–13.

Howlett, M. A., Berro, M. A., Abels, K., Bernacki, M., Panter, A., & Greene, J. (2025). Academic Coaches’ Perceptions of Coaching Students Enrolled in Introductory STEM Courses: An Exploratory Study. Journal of College Reading and Learning, 55(2), 161–178.

Berro, M. A., Ott, L., Garland, A., Evans, M., Hogan, K. A., Plumley, R. D., Kuhlmann, S., Yu, L., Bernacki, M., & Greene, J. (2025). Design matters: Students’ adherence to high-structure course design activities predicts their academic success. Journal of Educational Psychology. Published.

Lee, C., Luo, L., Kuhlmann, S., Plumley, R. D., Panter, A. T., Bernacki, M., Greene, J., & Gates, K. M. (2025). Interpretable Predictive Analytics for Online Learning: A Markov-Based Machine Learning Approach. Journal of Learning Analytics, 12(2), 259–278.

Yu, L., Halpin, P., Bernacki, M., Ren, S., Plumley, R. D., & Greene, J. (2025). Interpreting Predictive Learning Sequences in a College Math Course through a Self-Regulated Learning Framework. Journal of Learning Analytics, 12(3), 66–86.

Zhang, L., Carter, Jr, R. A., Bernacki, M., & Greene, J. (2025). Personalization, individualization, and differentiation: What do they mean and how do they differ for students with disabilities?. Exceptionality, 33(4), 241–262.

Hou, C., Kuhlmann, S., Greene, J., Bernacki, M., & Hogan, K. A. (2025). Process mining measures students’ help-seeking transitions when completing assignments in an online learning and assessment platform. Metacognition and Learning, 20(1), 40.

Ding, L., Windsor, E., Greene, J., Plumley, R. D., Ren, S., Stachura-Webb, N., Bernacki, M., & Hilpert, J. C. (2025). Using Students’ Motivation and Early Course Performance to Examine STEM Dropout: A Survival Analysis Approach. Journal of College Student Retention: Research, Theory \& Practice, 15210251251391367. 10.1177/15210251251391367

Wolff, S. M., Hilpert, J. C., Bernacki, M., Greene, J., & Strong, C. (2025). Using the fused graphical lasso to explore the motivational self-system after a multimedia self-regulated learning training: a brief research report. Frontiers in Psychology, 16, 1414563.

Bernacki, M., Yu, L., Kuhlmann, S., Plumley, R., Greene, J., Duke, R., Freed, R., Hollander-Blackmon, C., & Hogan, K. (2025). Using multimodal learning analytics to validate digital traces of self-regulated learning in a laboratory study and predict performance in undergraduate courses. Journal of Educational Psychology,, 117(2), 176–205. https://doi.org/10.1037/edu0000890

Walkington, C., Bernacki, M., Leyva, E., & Istas, B. (2025). When Am I (N)ever Going to Use This? How Algebraic Functions Are Used in STEM-Related Careers. Journal for Research in Mathematics Education, 56(2), 63–89. https://doi.org/10.5951/jresematheduc-2023-0091

Bernacki, M. (2025). Leveraging learning theory and analytics to produce grounded, innovative, data-driven, equitable improvements to teaching and learning. Journal of Educational Psychology, 117(1), 1–11. https://doi.org/10.1037/edu0000933

Deininger, H., Pieronczyk, I., Parrisius, C., Plumley, R. D., Meurers, D., Kasneci, G., Nagengast, B., Trautwein, U., Greene, J., & Bernacki, M. (2025). Using theory-informed learning analytics to understand how homework behavior predicts achievement. Journal of Educational Psychology, 117(1), 12–37. https://doi.org/10.1037/edu0000906

Walkington, C., Bernacki, M., Wang, M., Istas, B., & Greene, M. (2024). Posing mathematics problems about STEM careers: problem quality, scaffolds, and problem solving. International Journal of Mathematical Education in Science and Technology, 55. https://doi.org/10.1080/0020739X.2022.2128458

Wolff, S., Hilpert, J., Vongkulluksn, V., Bernacki, M., & Greene, J. (2024). Self-efficacy inertia: The role of competency beliefs and academic burden in achievement. Contemporary Educational Psychology, 79, 102315. https://doi.org/10.1016/j.cedpsych.2024.102315

Walkington, C., Bernacki, M., Vongkulluksn, V., Greene, M., Darwin, T., Leyva, E., Istas, B., Hunnicutt, J., Washington, J., & Wang, M. (2024). The effect of an intervention personalizing mathematics to students’ career and popular culture interests on mathematics interest and learning. Journal of Educational Psychology, 116(4), 506–531. https://doi.org/ttps://doi.org/10.1037/edu0000840

Zhang, L., Carter, R. A., Bernacki, M., & Greene, J. (2024). Personalization, Individualization, and Differentiation: What Do They Mean and How Do They Differ for Students with Disabilities?. Exceptionality, 1–22. https://doi.org/10.1080/09362835.2024.2446219

Walkington, C., Bernacki, M., Wang, M., Istas, B., & Greene, M. (2024). Posing mathematics problems about STEM careers: problem quality, scaffolds, and problem solving. International Journal of Mathematical Education in Science and Technology, 55(9), 2136–2169. https://doi.org/10.1080/0020739x.2022.2128458

Plumley, R. D., Bernacki, M., Greene, J., Kuhlmann, S., Raković, M., Urban, C. J., Hogan, K. A., Lee, C., Panter, A. T., & Gates, K. M. (2024). Co-designing enduring learning analytics prediction and support tools in undergraduate biology courses. British Journal of Educational Technology, 55(5), 1860–1883. https://doi.org/10.1111/bjet.13472

Kuhlmann, S., Plumley, R., Evans, Z., Bernacki, M., Greene, J., Hogan, K. A., Berro, M., Gates, K., & Panter, A. (2024). Students’ active cognitive engagement with instructional videos predicts STEM learning. Computers & Education, 216, 105050. https://doi.org/10.1016/j.compedu.2024.105050

Zhang, L., Carter, R. A., Greene, J., & Bernacki, M. (2024). Unraveling Challenges with the Implementation of Universal Design for Learning: A Systematic Literature Review. Educational Psychology Review, 36(1). https://doi.org/10.1007/s10648-024-09860-7

Sung, H., Bernacki, M., Greene, J., Yu, L., & Plumley, R. D. (2024). Beyond Frequency: Using Epistemic Network Analysis and Multimodal Traces to Understand Temporal Dynamics of Self-Regulated Learning. Journal of Science Education and Technology. Published. https://doi.org/10.1007/s10956-024-10164-2

Kuhlmann, S., Bernacki, M., & Greene, J. (2023). A multimedia learning theory-informed perspective on self-regulated learning. New Directions for Teaching and Learning, 2023(174), 17–23.

Kuhlmann, S. L., Bernacki, M. L., & Greene, J. A. (2023). A multimedia learning theory‐informed perspective on self‐regulated learning. New Directions for Teaching and Learning, 174, 17–23. https://doi.org/10.1002/tl.20544

Greene, J., Bernacki, M., Plumley, R. D., Kuhlmann, S., Hogan, K. A., Evans, M., Gates, K. M., & Panter, A. T. (2023). Investigating bifactor modeling of biology undergraduates’ task values and achievement goals across semesters. Journal of Educational Psychology, 115(6), 836–858. https://doi.org/10.1037/edu0000803

Hilpert, J. C., Greene, J., & Bernacki, M. (2023). Leveraging complexity frameworks to refine theories of engagement: Advancing self-regulated learning in the age of artificial intelligence. British Journal of Educational Technology, 54(5), 1204–1221.

Arizmendi, C., Bernacki, M., Rakovic, M., Plumley, R., Urban, C., Panter, A., Greene, J., & Gates, K. (2023). Predicting student outcomes using internet logs of learning behaviors: Review, current standards, and suggestions for future work. Behavioral Research Methods, 55, 306–3054. https://doi.org/10.3758/s13428-022-01939-9

Bernacki, M., Cogliano, M. C., Kuhlmann, S. L., Utz, J., Strong, C., J. C. H., & Greene, J. (2023). Relations between undergraduates’ self-regulated learning skill mastery during digital training and biology performance. Metacognition and Learning, 18, 711–774. https://doi.org/10.1007/s11409-023-09356-9

Kuhlmann, S., Bernacki, M., Greene, J., Hogan, K., Evans, M., Plumley, R. D., Gates, K. M., & Panter, A. T. (2023). How do students’ achievement goals relate to learning from well-designed instructional videos and subsequent exam performance?. Contemporary Educational Psychology., 73, 102162. https://doi.org/10.1016/j.cedpsych.2023.102162

Mefferd, K. C., & Bernacki, M. (2023). Tracing Undergraduate Science Learners’ Digital Cognitive Strategy Use and Relation to Performance. Journal of Science Education and Technology. Published. https://doi.org/10.1007/s10956-022-10018-9

Hilpert, J. C., Greene, J. A., & Bernacki, M. L. (2023). Leveraging complexity frameworks to refine theories of engagement: Advancing self‐regulated learning in the age of artificial intelligence. British Journal of Educational Technology, 54(5), 1204–1221. https://doi.org/10.1111/bjet.13340

Hilpert, J. C., Greene, J., & Bernacki, M. (2023). Leveraging complexity frameworks to refine theories of engagement: Advancing self‐regulated learning in the age of artificial intelligence. British Journal of Educational Technology, 54(5), 1204–1221. https://doi.org/10.1111/bjet.13340

Kuhlmann, S., Bernacki, M., & Greene, J. (2023). A multimedia learning theory‐informed perspective on self‐regulated learning. New Directions for Teaching and Learning, 2023(174), 17–23. https://doi.org/10.1002/tl.20544

Cogliano, M. C., Bernacki, M., & Hilpert, J. C. (2022). A Self-Regulated Learning Analytics Prediction-and-Intervention Design: Detecting and Supporting Struggling Biology Students. Journal of Educational Psychology, 114(8), 1801–1816. https://doi.org/10.1037/edu0000745

Rakovi\’c, Mladen, Bernacki, M., Greene, J., Plumley, R. D., Hogan, K. A., Gates, K. M., & Panter, A. T. (2022). Examining the critical role of evaluation and adaptation in self-regulated learning. Contemporary Educational Psychology, 68, 102027.

Leyva, E., Walkington, C., Perera, H., & Bernacki, M. (2022). Making Mathematics Relevant: An Examination of Student Interest in Math, Interest in STEM Careers, and Perceived Relevance. International Journal of Research in Undergraduate Mathematics Education. Published. https://link.springer.com/article/10.1007/s40753-021-00159-4

Walkington, C., Bernacki, M., Wang, M., Istas, B., & Greene, M. (2022). Posing Mathematics Problems about STEM Careers: Problem Quality, Scaffolds, and Problem Solving. Journal of Mathematical Education in Science & Technology. Journal of Mathematical Education in Science & Technology. Published. https://doi.org/10.1080/0020739X.2022.2128458

Arizmendi, C. J., Bernacki, M., Rakovi\’c, Mladen, Plumley, R. D., Urban, C. J., Panter, A., Greene, J., & Gates, K. M. (2022). Predicting student outcomes using digital logs of learning behaviors: Review, current standards, and suggestions for future work. Behavior Research Methods, 1–29.

Yu, L., Bernacki, M., Greene, J., Plumley, R. D., Duke, R. F., Freed, R., Gates, K. M., & Panter, A. T. (2022). Understanding College Students’ Self-Regulated Learning Using Process Mining. Companion Proceedings of the 12th, 45.

Leyva, E., Walkington, C., Perera, H., & Bernacki, M. (2022). Making Mathematics Relevant: an Examination of Student Interest in Mathematics, Interest in STEM Careers, and Perceived Relevance. International Journal of Research in Undergraduate Mathematics Education, 8(3), 612–641. https://doi.org/10.1007/s40753-021-00159-4

Huang, X., Bernacki, M., Ho, D., & Hong. (2022). Examining the role of self-efficacy and online metacognitive monitoring behaviors in undergraduate life science education. Learning and Instruction. Published. https://doi.org/doi.org/10.1016/j.learninstruc.2021.101577

Hong, W., & Bernacki, M. (2022). Initial and evolving perceptions of value and cost for the achievementand persistence of undergraduates pursuing science degrees. Journal of Educational Psychology. Published. https://doi.org/doi.org/10.1037/edu0000717

Bernacki, M. L., Greene, J., & Lobczowski, N. G. (2021). A Systematic Review of Research on Personalized Learning: Personalized by Whom, to What, How, and for What Purpose(s)?. Educational Psychology Review. Published. https://doi.org/10.1007/s10648-021-09615-8.

Hilpert, J. C., Bernacki, M., & Cogliano, M. C. (2021). Coping with the transition to remote instruction: patterns of self-regulated engagement in a large post-secondary biology course. Journal of Research on Technology in Education. Published. https://doi.org/doi.org/10.1080/15391523.2021.1936702

Leyva, E., Walkington, C., Perera, H., & Bernacki, M. (accepted). Making Mathematics Relevant: An Examination of Student Interest in Math, Interest in STEM Careers, and Perceived Relevance. International Journal of Research in Undergraduate Mathematics Education.

Greene, J., Plumley, R. D., Urban, C. J., Bernacki, M., Gates, K. M., Hogan, K. A., Demetriou, C., & Panter, A. T. (2021). Modeling temporal self-regulatory processing in a higher education biology course. Learning and Instruction, 72, 101201.

Greene, J., Urban, C. J., Plumley, R. D., Bernacki, M., Gates, K., Hogan, K., Demetriou, C., & Panter, A. (2021). Modeling temporal and contingent self-regulatory processing in a higher education biology course. Learning and Instruction, 72, 101201. https://doi.org/10.1016/j.learninstruc.2019.04.002

Crompton, H., Bernacki, M. L., & Greene, J. A. (2020). Psychological foundations of emerging technologies for teaching and learning in higher education. Current Opinion in Psychology, 36, 101–105. https://doi.org/10.1016/j.copsyc.2020.04.011

Crompton, H., Bernacki, M., & Greene, J. (2020). Psychological Foundations of Emerging Technologies for Teaching and Learning in Higher Education. Current Opinion in Psychology, 36, 101–105. https://doi.org/10.1016/j.copsyc.2020.04.011

Hong, W. J., Bernacki, M. L., & Perera, H. N. (2020). A latent profile analysis of undergraduates’ achievement motivations and metacognitive behaviors, and their relations to achievement in science. Journal of Educational Psychology, 112(7), 1409–1430. https://doi.org/10.1037/edu0000445

Cogliano, M. C., Bernacki, M., & Kardash, C. (accepted). A Metacognitive Retrieval Practice Intervention to Improve Undergraduates’ Monitoring and Control Processes and Use of Performance Feedback for Classroom Learning. Journal of Educational Psychology. http://dx.doi.org/10.1037/edu0000624

Walkington, C., & Bernacki, M. (2020). Appraising Research on Personalized Learning: Definitions, Theoretical Alignment, Advancements, and Future Directions. Journal of Research on Technology in Education, 52(3), 235–252. https://doi.org/10.1080/15391523.2020.1747757

Bernacki, M., Vosicka, L., & Utz, J. C. (2020). Can brief, web-delivered training help STEM undergraduates “learn to learn”?. Journal of Educational Psychology, 112(4), 765–781. https://doi.org/10.1037/edu0000405

Bernacki, M. L., Chavez, M. M., & Uesbeck, P. M. (2020). Predicting Achievement and Providing Support Before STEM Majors Begin to Fail. Computers & Education, 158. https://doi.org/10.1016/j.compedu.2020

Part, R., Perera, H. N., Marchand, G., & Bernacki, M. (2020). Revisiting the Dimensionality of Subjective Task Value: Towards Clarification of Competing Perspectives. Contemporary Educational Psychology, 62. https://doi.org/10.1016/j.cedpsych.2020.101875

Bernacki, M., Vosicka, L., Utz, J., & Bellomo, C. (accepted). Effects of Digital Learning Skill Training on the Academic Performance of Undergraduates in Science and Mathematics. Journal of Educational Psychology.

Bernacki, M., Greene, J., & Crompton, H. (2020). Mobile technology, learning, and achievement: Advances in understanding and measuring the role of mobile technology in education. Contemporary Educational Psychology, 60, 101827. https://doi.org/10.1016/j.cedpsych.2019.101827

Bernacki, M., Crompton, H., & Greene, J. (2020). Towards convergence of mobile and psychological theories of learning. Contemporary Educational Psychology, 60, 101828. https://doi.org/10.1016/j.cedpsych.2019.101828

Bernacki, M., Greene, J., & Crompton, H. (2019). Mobile Technology, Learning, and Achievement: Advances in Understanding and Measuring the Role of Mobile Technology in Education. Contemporary Educational Psychology, 101827.

Greene, J., Plumley, R. D., Urban, C. J., Bernacki, M., Gates, K. M., Hogan, K. A., Demetriou, C., & Panter, A. T. (2019). Modeling temporal self-regulatory processing in a higher education biology course. Learning and Instruction, 101201.

Bernacki, M., Crompton, H., & Greene, J. (2019). Towards Convergence of Mobile and Psychological Theories of Learning. Contemporary Educational Psychology, 101828.

Walkington, C., & Bernacki, M. (2019). Personalizing Algebra to Students’ Individual Interests in an Intelligent Tutoring System: Moderators of Impact. International Journal of Artificial Intelligence in Education, 29(1), 58–88. https://doi.org/10.1007/s40593-018-0168-1

Miller, C. J., & Bernacki, M. (2019). Training preparatory mathematics students to be high ability self-regulators: Comparative and case-study analyses of impact on learning behavior and achievement. High Ability Studies, 1–31. https://doi.org/10.1080/13598139.2019.1568829

Cogliano, M., Kardash, C. M., & Bernacki, M. (2019). The effects of retrieval practice and prior topic knowledge on test performance and confidence judgments. Contemporary Educational Psychology, 56, 117–129. https://doi.org/10.1016/j.cedpsych.2018.12.001

Winkelmes, M. A., Bernacki, M., Zochowski, M., Golanics, J., & Weavil, K. (2018). A Teaching intervention that increases underserved college students’ success,. Peer Review, 18(1/2), 31–36.

Richey, J. E., Bernacki, M., Belenky, D. M., & Nokes-Malach, T. J. (2018). Comparing Class- and Task-Level Measures of Achievement Goals. JOURNAL of EXPERIMENTAL EDUCATION, 86(4), 560–578. https://doi.org/10.1080/00220973.2017.1386155

Bernacki, M., & Walkington, C. (2018). The role of situational interest in personalized learning. Journal of Educational Psychology, 110(6), 864–881. https://doi.org/10.1037/edu0000250

Utz, J. C., & Bernacki, M. (2018). Voluntary Web-Based Self-Assessment Quiz Use is Associated With Improved Exam Performance, Especially for Learners with Low Prior Knowledge. HAPS Educator, 22(2), 129–135. https://doi.org/10.21692/haps.2018.021

Utz, J., & Bernacki, M. (2018). Voluntary Web-Based Self-Assessment Quiz Use is Associated With Improved Exam Performance, Especially for Learners with Low Prior Knowledge. HAPS Educator, 22(2), 129–135. https://doi.org/10.21692/haps.2018.021

Hilts, A., Part, R., & Bernacki, M. (2018). The roles of social influences on student competence, relatedness, achievement, and retention in STEM. Science Education, 102(4), 744–770. https://doi.org/10.1002/sce.21449

Volkert, D., Candela, L., & Bernacki, M. (2018). Student motivation, stressors, and intent to leave nursing doctoral study: A national study using path analysis. Nurse Education Today, 61, 210–215. https://doi.org/10.1016/j.nedt.2017.11.033

Walkington, C., & Bernacki, M. (2018). Personalization of Instruction: Design Dimensions and Implications for Cognition. The Journal of Experimental Education, 86(1), 50–68. https://doi.org/10.1080/00220973.2017.1380590

Schraw, G., & Bernacki, M. (2016). TEACHING INTRODUCTORY STATISTICS Challenges and Strategies. CHALLENGES and INNOVATIONS in EDUCATIONAL PSYCHOLOGY TEACHING and LEARNING, 305–319.

Bernacki, M. L., Nokes-Malach, T., Richey, J. E., & Belenky, D. M. (2016). Science diaries: a brief writing intervention to improve motivation to learn science. Educational Psychology, 36(1), 26–46. https://doi.org/10.1080/01443410.2014.895293

Walkington, C., & Bernacki, M. (2015). Students authoring personalized “algebra stories”: Problem-posing in the context of out-of-school interests. The Journal of Mathematical Behavior, 40, 171–191. https://doi.org/10.1016/j.jmathb.2015.08.001

Ben-Eliyahu, A., & Bernacki, M. (2015). Addressing complexities in self-regulated learning: a focus on contextual factors, contingencies, and dynamic relations. Metacognition and Learning, 10(1), 1–13. https://doi.org/10.1007/s11409-015-9134-6

Bernacki, M., Nokes-Malach, T. J., & Aleven, V. (2015). Examining self-efficacy during learning: variability and relations to behavior, performance, and learning. Metacognition and Learning, 10(1), 99–117. https://doi.org/10.1007/s11409-014-9127-x

Bernacki, M., Aleven, V., & Nokes-Malach, T. J. (2014). Stability and change in adolescents’ task-specific achievement goals and implications for learning mathematics with intelligent tutors. Computers in Human Behavior, 37, 73–80. https://doi.org/10.1016/j.chb.2014.04.009

Bernacki, M., Byrnes, J. P., & Cromley, J. G. (2012). The effects of achievement goals and self-regulated learning behaviors on reading comprehension in technology-enhanced learning environments. CONTEMPORARY EDUCATIONAL PSYCHOLOGY, 37(2), 148–161. https://doi.org/10.1016/j.cedpsych.2011.12.001

Book

Bernacki, M., Walkington, C., Emery, A., & Zhang, L. (Eds.). (2026). Handbook of Personalized Learning. Routledge. https://www.routledge.com/Handbook-of-Personalized-Learning/Bernacki-Walkington-Emery-Zhang/p/book/9781032719443

Book Chapter

Bernacki, M., & Walkington, C. (2026). An Extensible Model of Personalized Learning. In Handbook of Personalized Learning. https://www.routledge.com/Handbook-of-Personalized-Learning/Bernacki-Walkington-Emery-Zhang/p/book/9781032719443

Walkington, C., Bernacki, M. L., & Beauchamp, T. (2026). Personalizing Learning to Promote Interest. In Handbook of Personalized Learning. https://www.routledge.com/Handbook-of-Personalized-Learning/Bernacki-Walkington-Emery-Zhang/p/book/9781032719443

Greene, J., Hollander-Blackmon, C., & Bernacki, M. (2025). Learning to Monitor and Regulate Learning. In Handbook of Research on Learning and Instruction (pp. 183–202). Routledge.

Kuhlmann, S., Greene, J., & Bernacki, M. (2024). Online learning. Elsevier. https://doi.org/10.1016/B978-0-323-96023-6.00089-0

Loures-Elias, A. P. S., & Bernacki, M. (2024). The Influence of Affect in Help-Seeking Behaviors and Performance in a Math Intelligent Tutoring System. In S. Kadry (Ed.), Artificial Intelligence for Quality Education. Intech Open. https://doi.org/10.5772/intechopen.1004185

Greene, J., Bernacki, M., & Hadwin, A. (2024). Self-regulation. In Handbook of Educational Psychology (4th Edition): Vol. 4th (pp. 314–334). Routledge. https://doi.org/10.4324/9780429433726-17

Salehian Kia, F., Bernacki, M., & Greene, J. (2023). Measuring and Validating Assumptions About Self-Regulated Learning with Multimodal Data. In Advances in Analytics for Learning and Teaching (pp. 123–140). Springer International Publishing. https://doi.org/10.1007/978-3-031-30992-2_9

Greene, J., Bernacki, M., & Hadwin, A. F. (2023). Self-Regulation. In Handbook of Educational Psychology (pp. 314–334). Routledge. https://doi.org/10.4324/9780429433726-17

Huang, X., Hong, W., & Bernacki, M. (2018). The Psychological Cost of College Math: Digital Learning Behaviors, Outcomes, and Genders Differences. In Communications in Computer and Information Science (pp. 43–50). Springer International Publishing. https://doi.org/10.1007/978-3-319-92285-0_7

Walkington, C., & Bernacki, M. (2014). Motivating Students by “Personalizing” Learning around Individual Interests: A Consideration of Theory, Design, and Implementation Issues. In Advances in Motivation and Achievement (pp. 139–176). Emerald Group Publishing Limited. https://doi.org/10.1108/s0749-742320140000018004

Bernacki, M., Nokes, T. J., & Aleven, V. (2013). Fine-grained assessment of motivation over long periods of learning with an intelligent tutoring system: Methodology, advantages, and preliminary results. In International Handbook of Metacognition and Learning Technologies (pp. 629–644). Springer.

Byrnes, J. P., & Bernacki, M. (2012). Cognitive development and information behavior. In Children’s information behavior in the digital age. Scarecrow Press.

Bernacki, M., Aguilar, A., & Byrnes, J. P. (2011). Self-regulated learning and technology-enhanced learning environments: an opportunity propensity analysis. In Fostering self-regulated learning in ICTs (pp. 1–26). IGI Global Publishers.

Bernacki, M., & Bernt, F. M. (2007). Service-learning as a transformative experience: an analysis of the impact of service-learning on student attitudes and behaviors after two years of college. In From Passion to Objectivity: International and Cross-Disciplinary Perspectives on Service-Learning Research (pp. 111–134). Info Age.

Bernacki, M. L., & Bernt, F. M. (2007). Service-Learning as a Transformative Experience. In From Passion to Objectivity (pp. 111–134). Emerald Publishing Limited. https://doi.org/10.1108/978-1-60752-658-220251009

Conference Proceeding

Sung, H., Barro, M., Yu, L., Plumley, R. D., Bernacki, M., & Greene, J. (2024). Exploring the Relationship Between Students’ Adherence to Active Learning and Self-Regulated Learning Processes. Proceedings of the 18th International Conference of the Learning Sciences-ICLS 2024, Pp. 2361-2362. Published.

Howell, E., Bernacki, M., Walkington, C., & Istas, B. (2021). The connection between perception of utility in careers with math and STEM career interest. Karunakaran, S.S., Reed, Z., & Higgins, A. (Eds.), 1168–1169.

Istas, B., Walkington, C., Leyva, E., & Bernacki, M. L. (2021). When Am I (N)ever Going to Use This? How Engineers Use Algebra (NSF DRL). 2021 ASEE Virtual Annual Conference Content Access Proceedings. Published. https://doi.org/10.18260/1-2–38055

Hayes, D., Hong, W., Bernacki, M., & Voorhees, N. (2017). Using LMS Data to Provide Early Alerts to Struggling Students. 2017 FYEE Conference Proceedings. Published. https://doi.org/10.18260/1-2–29442

Other

Schwerter, J., Lauermann, F., Dimpfl, T., & Bernacki, M. L. (published). Retrieval Practice in Higher Education: Causality and Content Transfer Effects in a Gateway Math Course. In Journal of Educational Psychology. APA. https://doi.org/10.31234/osf.io/sj3w7_v1

Walkington, C., & Bernacki, M. (2021). Making Classroom Learning Personalized. In APA Division 15 Policy Brief Series. https://apadiv15.org/wp-content/uploads/2021/03/Policy-Brief-Making-Classroom-Learning-Personalized.pdf

Bernacki, M., Dai, T., & Part, R. (2017). Cross-Sectional, Longitudinal and Contextual Examination of Student Efficacy and Achievement Goals [Data set]. In PsycEXTRA Dataset. American Psychological Association (APA). https://doi.org/10.1037/e511122017-001

Walkington, C., & Bernacki, M. (2017). Attitudes Towards Algebra Measure [Data set]. In PsycTESTS Dataset. American Psychological Association (APA). https://doi.org/10.1037/t55359-000

Technical Report

Bernacki, M., & Perera, H. N. (2017). Encouraging young Nevadans to choose and stick with STEM careers: a choice and retention perspective on science, technology, engineering, and mathematics workforce development. In Policy Issues in Nevada Education: Vol. 1 (2nd ed.). UNLV.