Journal of Engineering Education Transformations

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The Impact of Cross-Cutting Pedagogical Features Based on Neuroeducation Advances: Project-Based Learning Vs. Traditional Lecturing in Engineering Education


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1 Industrial Engineering Department, Università Politecnica delle Marche, Ancona, Italy
     

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On the academic level of education, Traditional Lecturing represents the primary means of conveying information to the class. At the same time, Project-based learning is one of the major research subjects in engineering education, and literature claims it can offer more authentic and meaningful learning experiences. Supported by the most recent advances in syntheses of meta-analyses in education and neuroscientific-based educational sciences, the study presented compares Traditional Lecturing and two versions of Project-based learning implemented with variations in content and project typologies through a single-group variation on the two-group post-test-only randomized experiment. Two research hypotheses were investigated using three questionnaires and a test: I) the learning experience and outcomes are enhanced when attending Project-based learning lessons compared to Traditional Lecturing ones; II) effective cross-cutting instructional elements are more detectable in Project-based learning than in Traditional Lecturing and variations in contents and typologies of project do not lead to different outcomes within Project-based learning. The research was carried out in an Engineering course and involved 80 students. The results show that Project-based learning outperforms Traditional Lecturing and highlight the crucial role of some cross-cutting instructional features that are detectable or missing within the two methodologies. Derived from meta-analyses and neuroscientific-based educational sciences, these features represent a solid pedagogical core within the structure of the Project-based learning methodology. We argue they have a relevant role in the stability and enhancement of the results of Project-based learning in comparison with Traditional Lecturing. Indeed, despite variations in content and project typologies, Project-based learning produces similar results. Finally, for engineering teachers wishing to adopt Project-based learning, this study provides insights into the necessity to understand, consciously incorporate, support, and manipulate such particular features, especially through developing pedagogical competence based on scientific evidence.

Keywords

Neuroeducation, Engineering Education, Higher Education, Project-Based Learning, Traditional Lecturing.
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  • J. Hattie and G. C. R. Yates, Visible learning and the science of how we learn. Routledge, 2013.

  • L. Cuban, “Persistence of the inevitable: The teacher-centered classroom,” Educ. Urban Soc., vol. 15, no. 1, pp. 26–41, 1982.

  • J. Hattie, “Visible Learning. A Bradford Book.” Routledge, London, 2009.

  • M. Scardamalia and C. Bereiter, “Higher levels of agency for children in knowledge building: A challenge for the design of new knowledge media,”J.Learn. Sci.,vol.1,no.1,pp.37–68, 1991.

  • A. L. Brown, “Design experiments: Theoretical and methodological challenges in creating complex interventions in classroom settings,” J. Learn. Sci., vol. 2, no. 2, pp. 141–178, 1992.

  • S. A. Gallagher, W. J. Stepien, and H. Rosenthal, “The effects of problem-based learning on problem solving,” Gift. Child Q., vol. 36, no. 4, pp. 195–200, 1992.

  • M. J. Prince and R. M. Felder, “Inductive teaching and learning methods: Definitions, comparisons, and research bases,” J. Eng. Educ., vol. 95, no. 2, pp. 123–138, 2006.

  • J. W. Thomas, “A review of research on projectbased learning. Autodesk Foundation,” Retrieved April, 2000.

  • J. W. Thomas, Project based learning: A handbook for middle and high school teachers. Buck Institute for Education, 1999.

  • B. F. Jones, C. M. Rasmussen, and M. C. Moffitt, Real-life problem solving: A collaborative approach to interdisciplinary learning. American Psychological Association, 1997.

  • J. A. Hattie, “Visible learning: a synthesis of 800+ me t a - ana lys e s on a chi evement. Abingdon.” Routledge Abingdon, 2009.

  • J. Hattie, “Visible learning plus: 250+ influences on student achievement,” Visible Learn. plus, 2017.

  • M. S. C. Thomas, D. Mareschal, and I. Dumontheil, Educational neuroscience: development across the life span. Routledge, 2020.

  • T. N. Tokuhama-Espinosa, “The scientifically substantiated art of teaching: A study in the development of standards in the new academic field of neuroeducation (mind, brain, and education science),” Capella University, 2008.

  • M. S. Schwartz, V. Hinesley, Z. Chang, and J. M. Dubinsky, “Neuroscience knowledge enriches pedagogical choices,” Teach. Teach. Educ., vol. 83, pp. 87–98, 2019.

  • M. S. Amran, S. Rahman, S. SURAT, and A. Y. A. B. U. BAKAR, “Connecting neuroscience and education: Insight from neuroscience findings for better instructional learning,” J. Educ. Gift. Young Sci., vol. 7, no. 2, pp. 341–352, 2019.

  • E. Jensen and L. McConchie, Brain-based learning: Teaching the way students really learn. Corwin, 2020.

  • liz McDowell, “Effective teaching and learning on foundation and access courses in engineering, science and technology,” Eur. J. Eng. Educ., vol. 20, no. 4, pp. 417–425, 1995.

  • J. Sweller, P. Ayres, and S. Kalyuga, “Measuring cognitive load,” in Cognitive load theory, Springer, 2011, pp. 71–85.

  • J. Hattie, Visible learning for teachers: Maximizing impact on learning. Routledge, 2012.

  • S. Schrage, “Massive study finds lectures still dominate STEM education,” Fac. Focus, pp. 1–13, 2018.

  • L. Van Dijk, G. C. Van Der Berg, and H. Van Keulen, “Interactive lectures in engineering education,” Eur. J. Eng. Educ., vol. 26, no. 1, pp. 15–28, 2001.

  • K. Regmi, “A Review of Teaching Methods--Lecturing and Facilitation in Higher Education (HE): A Summary of the Published Evidence.,” J. Eff. Teach., vol. 12, no. 3, pp. 61–76, 2012.

  • S. L. Bretz, “Novak’s theory of education: Human constructivism and meaningful learning.” ACS Publications, 2001.

  • J. I. Goodlad, Aplace called school. Prospects for the future. ERIC, 1984.

  • J. Geake, The brain at school: Educational neuroscience in the classroom: Educational neuroscience in the classroom. McGraw-Hill Education (UK), 2009.

  • A. Guida, F. Gobet, H. Tardieu, and S. Nicolas, “How chunks, long-term working memory and templates offer a cognitive explanation for neuroimaging data on expertise acquisition: a two-stage framework,” Brain Cogn., vol. 79, no. 3, pp. 221–244, 2012.

  • T. Tokuhama-Espinosa, The new science of teaching and learning: Using the best of mind, brain, and education science in the classroom. Teachers College Press, 2015.

  • W. Jochems, “Good practice, wat is de praktijk en wat is goed?[Good practice, what is the teaching practice and what is good?],” Onderz. van Onderwijs, vol. 25, pp. 4–5, 1996.

  • R. K. Chowdhury, “Learning and teaching style assessment for improving project-based learning of engineering students: A case of United Arab Emirates University,” Australas. J. Eng. Educ., vol. 20, no. 1, pp. 81–94, 2015.

  • J. Fitzpatrick, K. Cronin, and E. Byrne, “Is attending lectures still relevant in engineering education?,” Eur. J. Eng. Educ., vol. 36, no. 3, pp. 301–312, 2011.

  • E. Bales, “Corporate Universities versus traditional Universities. Keynote at the Conference on innovative practices in business education.” Orlando, Florida, December, 1996.

  • J. Rutkowski and K. Moscinska, “ICT supported engineering course--case study and guidelines,” in Proc. 12th IASTED Int. Conf. on Computers and Advanced Technology in Education (CATE), 2009, pp. 129–136.

  • L. A. Van Dijk and W. M. G. Jochems, “Changing a traditional lecturing approach into an interactive approach: Effects of interrupting the monologue in lectures,” Int. J. Eng. Educ., vol. 18, no. 3, pp. 275–284, 2002.

  • W. E. Forum, “The Future of Jobs Report 2020,” 2020.

  • D. R. Krathwohl, “A revision of Bloom’s taxonomy: Krathwohl, D. R. (2002). A revision of Bloom’s taxonomy: An overview. Theory into Practice, 41(4), 212–218.An overview,” Theory Pract., vol. 41, no. 4, pp. 212–218, 2002.

  • K. Alanne, “An overview of game-based learning in building services engineering education,” Eur. J. Eng. Educ., vol. 41, no. 2, pp. 204–219, 2016.

  • Y.-Y. Tang, Brain-based learning and education: Principles and practice. Academic Press, 2017.

  • I. Mayer, H. Warmelink, and G. Bekebrede, “Learning in a game-based virtual environment: a comparative evaluation in higher education,” Eur. J. Eng. Educ., vol. 38, no. 1, pp. 85–106, 2013.

  • C. A. Bodnar, D. Anastasio, J. A. Enszer, and D. D. Burkey, “Engineers at play: Games as teaching tools for undergraduate engineering students,” J. Eng. Educ., vol. 105, no. 1, pp. 147–200, 2016.

  • P. C. Blumenfeld, E. Soloway, R. W. Marx, J. S. Krajcik, M. Guzdial, and A. Palincsar, “Motivating project-based learning: Sustaining the doing, supporting the learning,” Educ. Psychol., vol. 26, no. 3–4, pp. 369–398, 1991.

  • B. J. S. Barron et al., “Doing with understanding: Lessons from research on problem-and project-based learning,” J. Learn. Sci., vol. 7, no. 3–4, pp. 271–311, 1998.

  • C. Bereiter and M. Scardamalia, “Process and product in PBL research,” Toronto Ontario Institutes Stud. Educ. Toronto, 1999.

  • J. S. Brown, A. Collins, and P. Duguid, “Situated cognition and the culture of learning,” Educ. Res., vol. 18, no. 1, pp. 32–42, 1989.

  • J. Boaler, “Open and closed mathematics: Student experiences and understandings,” J. Res. Math. Educ., pp. 41–62, 1998.

  • M. Prince, “Does active learning work? Areview of the research,” J. Eng. Educ., vol. 93, no. 3, pp. 223–231, 2004.

  • R. W. Marx, P. C. Blumenfeld, J. S. Krajcik, and E. Soloway, “Enacting project-based science,” Elem. Sch. J., vol. 97, no. 4, pp. 341–358, 1997.

  • D. Kokotsaki, V. Menzies, and A. Wiggins, “Project-based learning: A review of the literature,” Improv. Sch., vol. 19, no. 3, pp. 267–277, 2016.

  • C. Zhou, A. Kolmos, and J. F. D. Nielsen, “A problem and project-based learning (PBL) approach to motivate group creativity in engineering education,” Int. J. Eng. Educ., vol. 28, no. 1, pp. 3–16, 2012.

  • J. P. T. Mo and Y. M. Tang, “Project-based learning of systems engineering V model with the support of 3D printing,” Australas. J. Eng. Educ., vol. 22, no. 1, pp. 3–13, 2017.

  • A. M. Ruiz-Ortega, J. J. Gallardo-Rodr’iguez, E. Navarro-López, and M. del Carmen Cerón-Garc’ia, “Project-led-education experience as a partial strategy in first years of engineering courses,” Educ. Chem. Eng., vol. 29, pp. 1–8, 2019.

  • M. Gibbes and L. Carson, “Project-based language learning: an activity theory analysis,” Innov. Lang. Learn. Teach., vol. 8, no. 2, pp. 171–189, 2014.

  • R. A. Stewart, “Investigating the link between self directed learning readiness and project-based learning outcomes: the case of international Masters students in an engineering management course,” Eur. J. Eng. Educ., vol. 32, no. 4, pp. 453–465, 2007.

  • P. T. Terenzini, A. F. Cabrera, C. L. Colbeck, J. M. Parente, and S. A. Bjorklund, “Collaborative learning vs. lecture/discussion: Students’ reported learning gains,” J. Eng. Educ., vol. 90, no. 1, pp. 123–130, 2001.

  • R. G. Hadgraft and A. Kolmos, “Emerging learning environments in engineering education,” Australas. J. Eng. Educ., vol. 25, no. 1, pp. 3–16, 2020.

  • M. Frank, I. Lavy, and D. Elata, “Implementing the project-based learning approach in an academic engineering course,” Int. J. Technol. Des. Educ., vol. 13, no. 3, pp. 273–288, 2003.

  • W. M. K. Trochim and J. P. Donnelly, Research methods knowledge base, vol. 2. Atomic Dog Pub., 2001.

  • W. A. Edmonds and T. D. Kennedy, An applied guide to research designs: Quantitative, qualitative, and mixed methods. Sage Publications, 2016.

  • L. Cohen, L. Manion, and K. Morrison, Research methods in education. routledge, 2017.

  • K. J. Flannelly, L. T. Flannelly, and K. R. B. Jankowski, “Threats to the internal validity of experimental and quasi-experimental research in healthcare,” J. Health Care Chaplain., vol. 24, no. 3, pp. 107–130, 2018.

  • D. Watson, L. A. Clark, and A. Tellegen, “Development and validation of brief measures of positive and negative affect: the PANAS scales.,” J. Pers. Soc. Psychol., vol. 54, no. 6, p. 1063, 1988.

  • L. M. Aleamoni, “Student rating myths versus research facts from 1924 to 1998,” J. Pers. Eval. Educ., vol. 13, no. 2, pp. 153–166, 1999.

  • P. Ramsden and E. Martin, “Recognition of good university teaching: Policies from an Australian study,” Stud. High. Educ., vol. 21, no. 3, pp. 299–315, 1996.

  • K. Trigwell, M. Prosser, and F. Waterhouse, “Relations between teachers’ approaches to teaching and students’ approaches to learning,” High. Educ., vol. 37, no. 1, pp. 57–70, 1999.

  • K. Trigwell, “Judging university teaching,” Int. J. Acad. Dev., vol. 6, no. 1, pp. 65–73, 2001.

  • S. Bradley, E. Kirby, and M. Madriaga, “What students value as inspirational and transformative teaching,” Innov. Educ. Teach. Int., vol. 52, no. 3, pp. 231–242, 2015.

  • Y. Hill, L. Lomas, and J. MacGregor, “Students’ perceptions of quality in higher education,” Qual. Assur. Educ., 2003.

  • H. F. Kaiser, “An index of factorial simplicity,” Psychometrika, vol. 39, no. 1, pp. 31–36, 1974.

  • J. F. Hair Jr, “Black, WC/Babin, BJ/Anderson, RE & Tatham, RL (2006): Multivariate Data Analysis,” Auflage, Up. Saddle River, 2006.

  • Y. L. Shing and G. Brod, “Effects of prior knowledge on memory: Implications for education,” Mind, Brain, Educ., vol. 10, no. 3, pp. 153–161, 2016.

  • T. Harland, “Vygotsky’s zone of proximal development and problem-based learning: Linking a theoretical concept with practice through action research,” Teach. High. Educ., vol. 8, no. 2, pp. 263–272, 2003.

  • E. Gozuyesil and A. Dikici, “The Effect of Brain Based Learning on Academic Achievement: A Meta-Analytical Study.,” Educ. Sci. Theory Pract., vol. 14, no. 2, pp. 642–648, 2014.

  • J. Hattie and S. Clarke, Visible Learning: Feedback. Routledge, 2018.

  • P. A. Kirschner, J. Sweller, and R. E. Clark, “Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching,” Educ. Psychol., vol. 41, no. 2, pp. 75–86, 2006.

  • D. Sloan and C. Norrgran, “A neuroscience perspective on learning,” Chem. Eng. Educ., vol. 50, no. 1, pp. 29–37, 2016.

  • G. L. Adams and S. Engelmann, Research on direct instruction: 25 years beyond DISTAR. ERIC, 1996.

  • T. R. Guskey and T. D. Pigott, “Research on group-based mastery learning programs: A meta-analysis,” J. Educ. Res., vol. 81, no. 4, pp. 197–216, 1988.

  • R. M. Ryan and E. L. Deci, “Intrinsic and extrinsic motivation from a self-determination theory perspective: Definitions, theory, practices, and future directions,” Contemp. Educ. Psychol., vol. 61, p. 101860, 2020.

  • D. P. Ausubel, “The Adquisition and Retention of Knowledge. Dortrecht, Netherlands,” Kluwer, vol. 10, pp. 978–994, 2000.

  • E. L. Deci and R. M. Ryan, “Human autonomy,” in Efficacy, agency, and self-esteem, Springer, 1995, pp. 31–49.

  • V. McGrath, “Reviewing the Evidence on How Adult Students Learn: An Examination of Knowles’ Model of Andragogy.,” Adult Learn. Irish J. Adult Community Educ., vol. 99, p. 110, 2009.

  • M. R. Lepper, “Motivational considerations in the study of instruction,” Cogn. Instr., vol. 5, no. 4, pp. 289–309, 1988.

  • T. W. Malone, “Making learning fun: A taxonomic model of intrinsic motivations for learning,” Conative Affect. Process Anal., 1987.

  • E. L. Deci and R. M. Ryan, “Intrinsic motivation and self-determination in human behavior: Springer Science & Business Media,” 1985.

  • B. Galand, B. Raucent, and M. Frenay, “Engineering students’ self-regulation, study strategies, and motivational believes in traditional and problem-based curricula,” Int. J. Eng. Educ., vol. 26, no. 3, pp. 523–534, 2010.

  • S. R. Hall, I. Waitz, D. R. Brodeur, D. H. Soderholm, and R. Nasr, “Adoption of active learning in a lecture-based engineering class,” in 32nd Annual frontiers in education, 2002, vol. 1, pp. T2A--T2A.

  • L. S. Vygotsky, Mind in society: The development of higher psychological processes. Harvard university press, 1980.

  • A. N. Kluger and A. DeNisi, “The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory.,” Psychol. Bull., vol. 119, no. 2, p. 254, 1996.

  • D. R. Sadler, “Formative assessment and the design of instructional systems,” Instr. Sci., vol. 18, no. 2, pp. 119–144, 1989.

  • R. W. Lent, D. Singley, H.-B. Sheu, J. A. Schmidt, and L. C. Schmidt, “Relation of socialcognitive factors to academic satisfaction in engineering students,” J. Career Assess., vol. 15, no. 1, pp. 87–97, 2007.

  • M. J. S. Gan and J. Hattie, “Prompting secondary students’use of criteria, feedback specificity and feedback levels during an investigative task,” Instr. Sci., vol. 42, no. 6, pp. 861–878, 2014.

  • A. C. Alves, D. Mesquita, F. Moreira, and S. Fernandes, “Teamwork in Project-Based Learning: engineering students’ perceptions of strengths and weaknesses,” in Proceedings of the Fourth International Symposium on Project Approaches in Engineering Education (PAEE’2012), 2012, pp. 23–32.

  • B. A. Oakley, D. M. Hanna, Z. Kuzmyn, and R. M. Felder, “Best practices involving teamwork in the classroom: Results from a survey of 6435 engineering student respondents,” IEEE Trans. Educ., vol. 50, no. 3, pp. 266–272, 2007.

  • K. J. Chua, W. M. Yang, and H. L. Leo, “Enhanced and conventional project-based learning in an engineering design module,” Int. J. Technol. Des. Educ., vol. 24, no. 4, pp. 437–458, 2014.

  • S. Chandrasekaran, A. Stojcevski, G. Littlefair, and M. Joordens, “Learning through projects in engineering education,” 2012.

  • J. Hattie, Visible learning: A synthesis of over 800 meta-analyses relating to achievement. Routledge, 2008.

  • All ENTER Consortium members, “Engineering Educators’ Pedagogical Training in Europe, Russia and Kazakhstan: background, best practices, challenges and opportunities,” 2019. http://erasmus-enter.org/files/r_1.3_-_best_practices_of_pedagogical_education_for_engineering_teachers__(e-book).pdf

  • U . A . K azakova and I. A. Alekhin, “Psychological and pedagogical training of teachers of engineering universities in the framework of additional professional education,” in Proceedings of the Conference “Integrating Engineering Education and Humanities for Global Intercultural Perspectives,” 2020, pp. 569–577.

  • S. Kersten, “Approaches of engineering pedagogy to improve the quality of teaching in engineering education,” in Vocational Teacher Education in Central Asia, Springer, Cham, 2018, pp. 129–139.


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  • The Impact of Cross-Cutting Pedagogical Features Based on Neuroeducation Advances: Project-Based Learning Vs. Traditional Lecturing in Engineering Education

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Authors

Claudia Paciarotti
Industrial Engineering Department, Università Politecnica delle Marche, Ancona, Italy
Gabriele Bertozzi
Industrial Engineering Department, Università Politecnica delle Marche, Ancona, Italy

Abstract


On the academic level of education, Traditional Lecturing represents the primary means of conveying information to the class. At the same time, Project-based learning is one of the major research subjects in engineering education, and literature claims it can offer more authentic and meaningful learning experiences. Supported by the most recent advances in syntheses of meta-analyses in education and neuroscientific-based educational sciences, the study presented compares Traditional Lecturing and two versions of Project-based learning implemented with variations in content and project typologies through a single-group variation on the two-group post-test-only randomized experiment. Two research hypotheses were investigated using three questionnaires and a test: I) the learning experience and outcomes are enhanced when attending Project-based learning lessons compared to Traditional Lecturing ones; II) effective cross-cutting instructional elements are more detectable in Project-based learning than in Traditional Lecturing and variations in contents and typologies of project do not lead to different outcomes within Project-based learning. The research was carried out in an Engineering course and involved 80 students. The results show that Project-based learning outperforms Traditional Lecturing and highlight the crucial role of some cross-cutting instructional features that are detectable or missing within the two methodologies. Derived from meta-analyses and neuroscientific-based educational sciences, these features represent a solid pedagogical core within the structure of the Project-based learning methodology. We argue they have a relevant role in the stability and enhancement of the results of Project-based learning in comparison with Traditional Lecturing. Indeed, despite variations in content and project typologies, Project-based learning produces similar results. Finally, for engineering teachers wishing to adopt Project-based learning, this study provides insights into the necessity to understand, consciously incorporate, support, and manipulate such particular features, especially through developing pedagogical competence based on scientific evidence.

Keywords


Neuroeducation, Engineering Education, Higher Education, Project-Based Learning, Traditional Lecturing.

References