Categories: Arts | Cognitive Science | Computing | Emotions and Learning from Failure | Engineering | Entrepreneurship and Business | Humanities | Math | Power and Privilege of Failure / Structural Supports | Science | Social Sciences | Problem-based Learning

Arts

Smith, S., & Henriksen, D. (2016). Fail Again, Fail Better: Embracing Failure as a Paradigm for Creative Learning in the Arts. Art Education (Reston), 69(2), 6–11. https://doi.org/10.1080/00043125.2016.1141644 

A discussion of failure’s centrality to creative process and of the value of allowing failure in arts education. Discussion critically synthesizes insights from United States educational policy, evolutionary psychology and the psychology of learning, and a narrative case study from a technology-based teacher education course exploring arts-based approaches for integrating new media into various K-12 learning contexts.  

Thorley, M. (2018). The role of failure in developing creativity in professional music recording and production. Thinking Skills and Creativity, 30, 160–170. https://doi.org/10.1016/j.tsc.2018.05.002 

An article detailing the application of a “productive failure” lens to the learning of professional music recording and production. The study involved music technology students in a music production task assessed by an industry professional and discussed in in-depth follow-up interviews, and demonstrated, among other things, the value of self-reflection for the development of technical skills and creative vision.    

Cognitive Science

Bjork RA. Memory and metamemory considerations in the training of human beings. (1994). In: Metcalfe JA, Shimamura AP (Eds), Metacognition: Knowing about Knowing. 1st Ed. Cambridge, MA: MIT Press. p 185–205. https://doi.org/10.7551/mitpress/4561.003.0011 

In this chapter, the author discusses some peculiarities of human memory that affect the ways we store and retrieve information, and applies these insights to an examination of optimal conditions for the transferability (endurance and accessibility) of knowledge and skills acquired during training to post-training contexts.  

Bjork R.A, & Bjork E.L. (2011). Making things hard on yourself, but in a good way: Creating desirable difficulties to enhance learning. In Gernsbacher M.A., Pew R.W., Hough L.M., Pomerantz J.R. (Eds), Psychology and the Real World: Essays Illustrating Fundamental Contributions to Society. (1st ed., pp. 56–64). Worth Publishers.  

The authors distinguish between performance and learning to elaborate on the ways introducing difficulty into learning conditions leads to more durable and flexible learning. Examples of “desirable difficulties” discussed include varying the conditions of learning; interleaving instruction on separate topics, rather than grouping instruction by topic; spacing, rather than massing, study sessions on a given topic; and using tests, rather than presentations, as study events. 

Dobson, J. L., & Linderholm, T. (2015). The effect of selected “desirable difficulties” on the ability to recall anatomy information. Anatomical Sciences Education, 8(5), 395–403. https://doi.org/10.1002/ase.1489. 

An application of the cognitive scientific concept of “desirable difficulties” to the domain of anatomical learning. Findings demonstrated that an effortful retrieval task (self-testing) proved most beneficial for both short- and long-term recall. 

Computing

Blumberg, F. C., Rosenthal, S. F., & Randall, J. D. (2008). Impasse-driven learning in the context of video games. Computers in Human Behavior, 24(4), 1530–1541. https://doi.org/10.1016/j.chb.2007.05.010. 

An analysis of problem-solving skills used by frequent and infrequent video game players to negotiate impasses encountered while playing a novel video game. Applicability to learning and instruction in academic settings briefly discussed.  

Emotions and Learning from Failure 

D’Mello, S., & Graesser, A. (2012). Dynamics of affective states during complex learning. Learning and Instruction, 22(2), 145–157. https://doi.org/10.1016/j.learninstruc.2011.10.001. 

Theoretical frameworks treating affective and cognitive states during complex learning are emerging in psychology, education, and artificial intelligence in education. Here, a model is proposed for the changing affective states emerging during deep learning activities, and the results of two studies supporting the major hypotheses of this model are analyzed. Oscillations between confusion-engagement/flow states, boredom-frustration states and confusion-frustration states are discussed, as are pedagogical strategies inspired by this model. 

Oades-Sese, G.V., Matthews, T.A. And Lewis, M. Shame and Pride and Their Effects on Student Achievement. (2014). In International Handbook of Emotions in Education (pp. 256–274). Routledge. https://doi.org/10.4324/9780203148211-19. 

This chapter offers a critical analysis of shame and pride as encountered within early learning contexts, couched within larger discussion of the role of emotions in learning.  

Pekrun, R., Goetz, T., Perry, R. P., Kramer, K., Hochstadt, M., & Molfenter, S. (2004). Beyond test anxiety: Development and validation of the test emotions questionnaire (TEQ). Anxiety, Stress, and Coping, 17(3), 287–316. https://doi.org/10.1080/10615800412331303847. 

While anxiety dominates scholarship on test emotions, findings here challenge its centrality. The authors discuss their development of a multi-scale questionnaire (Test Emotions Questionnaire, TEQ) to assess test-related joy, hope, pride, relief, anger, anxiety, shame, and hopelessness.   

Shepherd, D. A., Patzelt, H., & Wolfe, M. (2011). Moving Forward from Project Failure: Negative Emotions, Affective Commitment, and Learning from the Experience. Academy of Management Journal, 54(6), 1229–1259. https://doi.org/10.5465/amj.2010.0102.  

An analysis of responses to project failure as products of a) individual coping orientations, b) the normalization of failure within an organization (and individual affective commitments to said organization), and c) a sense-making logic that combines insights from both of these domains.  

Walsh, B. (2019). Frustration Is a Feature: Ugly Feelings and the Digital Humanities. Pedagogy: Critical Approaches to Teaching Literature, Language, Culture, and Composition, 19(3), 519–524. https://doi.org/10.1215/15314200-7615485. 

This article draws from Sianne Ngai’s theorization of “ugly feelings” and the author’s experiences with digital humanities instruction to offer an argument and strategies for centering emotional work (especially involving frustration and anxiety) in the classroom. 

Engineering 

Searle, K. A., Litts, B. K., & Kafai, Y. B. (2018). Debugging open-ended designs: High school students’ perceptions of failure and success in an electronic textiles design activity. Thinking Skills and Creativity, 30, 125–134. https://doi.org/10.1016/j.tsc.2018.03.004. 

Findings from an eight-week long workshop with 16 high school freshmen (13–15 years) engaged in an open-ended design task (involving computing and engineering) with electronic textile materials. Contributes to the growing work on productive failure as a learning design with applicability to open-ended design tasks. 

Oh, M., & Lawson, F. (2020). The Engineering Ed project: dealing with failure and the robotic future–engaging students in multidisciplinary STEM learning. School Science Review, 101(376), 51-56. 

This article details workshops designed for primary school students by a team of engineers, education specialists, trainee teachers and educations researchers to challenge misperceptions about engineering and standard school experiences in STEM (which tend to promote “recipe investigations” with a single correct method and solution). It proposes the use of similar projects for multidisciplinary learning (including dealing with failure) across the secondary school curriculum and offers practical suggestions about how such sessions might be delivered. 

Entrepreneurship and Business 

Edmondson, A. C. (2011). Strategies for Learning from Failure. Harvard Business Review, 89(4). https://www.hbs.edu/faculty/Pages/item.aspx?num=40142. 

A professor at Harvard Business School, the author of this article encourages executives to a) accept that failure is inevitable in complex work organizations and b) develop a “learning culture” that encourages active reflection on reported failures and fosters experimentation.  Offers an analysis of three different types of failure and emphasizes that successful learning from failure requires context-specific strategies. 

Rami, U., & Gould, C. (2016). From a “Culture of Blame” to an Encouraged “Learning from Failure Culture.” Business Perspectives and Research, 4(2), 161–168. https://doi.org/10.1177/2278533716642651. 

Based on a research in two Austrian companies, this article discusses the development of a constructive error culture in an organization, highlighting cultural factors which support or inhibit “learning from failure.”  

Ucbasaran, D., Shepherd, D. A., Lockett, A., & Lyon, S. J. (2013). Life After Business Failure: The Process and Consequences of Business Failure for Entrepreneurs. Journal of Management, 39(1), 163–202. https://doi.org/10.1177/0149206312457823. 

This article reviews (and develops a schema for organizing) research on life after business failure for entrepreneurs. It examines financial, social, and psychological costs of failure, research that explains how entrepreneurs make sense of and learn from failure, and research on the outcomes of business failure, including recovery as well as cognitive and behavioral outcomes.  

Fang He, V., Sirén, C., Singh, S., Solomon, G., & von Krogh, G. (2018). Keep Calm and Carry On: Emotion Regulation in Entrepreneurs’ Learning from Failure. Entrepreneurship Theory and Practice, 42(4), 605–630. https://doi.org/10.1177/1042258718783428. 

This paper draws on affective events theory to develop a model showing the impact of “failure velocity” on entrepreneurs’ learning from failure. Survey data from entrepreneurs in the information technology industry in the United States and Finland suggests that emotion regulation is key to sustained learning when failure velocity is high. The authors call for further research and training on the interplay of cognition and emotion in entrepreneurial learning. 

Humanities 

Elden, S. (2005). The problem of confession: the productive failure of Foucault’s History of Sexuality. Journal for Cultural Research, 9(1), 23–41. https://doi.org/10.1080/1479758042000331925. 

A “productive failure” lens applied to a massively influential critical theoretical work with extensive reach (both within and beyond the humanities). Synthesizing recently published lecture courses, materials archived in Paris and the full range of the writings published in Foucault’s life to trace a history of Foucault’s plans for his (unfinished) last major project, the History of Sexuality, this article argues that Foucault’s failure to accomplish the project as originally laid out was productive in its own right.  

Stommel, Jesse. “The Digital Humanities Is About Breaking Stuff.” Hybrid Pedagogy (blog), September 2, 2013. https://hybridpedagogy.org/the-digital-humanities-is-about-breaking-stuff/. 

A blog post detailing the author’s perspective on the crucial role of “breaking stuff” within the digital humanities, especially at the undergraduate level. The post concludes with sample responses to an assignment asking students to “break something” (in this case, a poem by Emily Dickinson) “as an act of literary criticism.” One of the student responses documents the process, complementing the post’s reflections on pedagogical processes of destruction and (re)creation.  

Math 

Barbieri, C. A., & Booth, J. L. (2020). Mistakes on display: Incorrect examples refine equation solving and algebraic feature knowledge. Applied Cognitive Psychology, 34(4), 862–878. https://doi.org/10.1002/acp.3663. 

A study of middle school algebra students assessing the effects of examples featuring either errors or correct concepts and procedures on algebraic feature knowledge and solving quadratic equations. Findings show that studying and explaining common errors displayed in incorrect examples improved equation-solving ability.  

Kapur, M. (2016). Examining Productive Failure, Productive Success, Unproductive Failure, and Unproductive Success in Learning. Educational Psychologist, 51(2), 289–299. https://doi.org/10.1080/00461520.2016.1155457. 

Proceeding from the postulate that “performance and learning are not always commensurable,” especially in the short versus long term, Kapur interrogates four distinct possibilities for design of initial learning: what he calls productive success, productive failure, unproductive failure success and unproductive failure.  

Kapur, M. (2014). Productive Failure in Learning Math. Cognitive Science, 38(5), 1008–1022. https://doi.org/10.1111/cogs.12107. 

An examination of two randomized-controlled studies that demonstrated heightened conceptual understanding and capacity to transfer knowledge in learners who solved problems before receiving instruction in the process of learning new math concepts. Results challenge the dominance of direct instruction in math learning, and the author proposes learning from failed attempts before receiving instruction as an alternative to direct instruction.  

Tulis, M., & Ainley, M. (2011). Interest, enjoyment and pride after failure experiences? Predictors of students’ state-emotions after success and failure during learning in mathematics. Educational Psychology (Dorchester-on-Thames), 31(7), 779–807. https://doi.org/10.1080/01443410.2011.608524. 

Analysis of two studies treating students’ emotional responses to experiences of success and failure in an individualised computer-based mathematics learning environment. Central to the analysis is the relation of these emotional responses to student self-concept of ability, subject value and orientation to learning from errors (in Study 1) as well as to students’ goal orientation and their causal attributions for success in school (in Study 2).  

Tulis, M. (2013). Error management behavior in classrooms: Teachers’ responses to student mistakes. Teaching and Teacher Education, 33, 56–68. https://doi.org/10.1016/j.tate.2013.02.003. 

An analysis of the interplay between “error climate” in classrooms and students’ beliefs about making (and learning from) mistakes, based on data from three studies (including direct and videotaped observation of error management behaviour as well as students’ self-reports). Among other findings, demonstrates that teachers’ routine responses to errors substantially affect students’ perceptions of errors as potential learning opportunities.  

Tulis, M., Steuer, G., & Dresel, M. (2018). Positive beliefs about errors as an important element of adaptive individual dealing with errors during academic learning. Educational Psychology (Dorchester-on-Thames), 38(2), 139–158. https://doi.org/10.1080/01443410.2017.1384536. 

A study based on data collected from six hundred and fourteen grade 5–7 students  from Austrian and German secondary schools, demonstrating the effects of positive error-related beliefs on reactions to errors (in terms of affects-motivations and adaptive actions).  

Power and Privilege of Failure / Structural Supports 

Feigenbaum, P. (2021). Telling Students it’s O.K. to Fail, but Showing Them it Isn’t: Dissonant Paradigms of Failure in Higher Education. Teaching and Learning Inquiry, 9(1), 13–26. https://doi.org/10.20343/teachlearninqu.9.1.3 

The author highlights the dissonance between the discourses of generative failure increasingly common in higher education and the stigmatized failure systemically produced in institutions of higher learning and experienced as such by students. He advocates for “wise interventions” that explicitly address the systemic roots of stigmatized failure and discourage (through instructional design) the hypercompetitive individualism contributing to stigmatized failure.  

Hallmark, T. (2018). When “failure is ok” is not ok. The Chronicle of Higher Education, 64(23), A44. 

A critique of blanket attempts to normalize failure that do not address matters of privilege, power, and positionality.  A concise treatment of the ways low-income students, first-generation students, and other marginalized students cannot afford to fail. Offers practical suggestions about how best to support such students in higher education at individual and systemic levels.  

Kundu, A. (2014). Backtalk: Grit, overemphasized; agency, overlooked. Phi Delta Kappan 96(1), 80. https://doi.org/10.1177/0031721714547870 

A critique of discourses celebrating “grit” as essential to academic success. The author argues that overemphasizing grit obscures many of the structural issues affecting student learning and oversimplifies the problems facing educators and institutions of learning today. “Agency” is proposed a preferable term, as a trait that is not confined to the individual but can describe collective efforts towards collective interests.  

Science 

Henry, M. A., Shorter, S., Charkoudian, L., Heemstra, J. M., & Corwin, L. A. (2019). “FAIL” Is Not a Four-Letter Word: A Theoretical Framework for Exploring Undergraduate Students’ Approaches to Academic Challenge and Responses to Failure in STEM Learning Environments. CBE—Life Sciences Education, 18(1), ar11–ar11. https://doi.org/10.1187/cbe.18-06-0108 

This study notes a dearth of scholarship on how STEM students develop the skills and dispositions needed to persevere through challenges and contend with failure, despite these being hallmark traits of successful scientists. Drawing from broader research on mindset, goal orientations, attributions, fear of failure, and coping, the authors generate a model of hypothetical responses to failures in undergraduate STEM learning contexts.  The goal is to facilitate understanding (and encourage critical discussion around) challenge-engaging dispositions, adaptive coping with failure, and how these might be encouraged and developed in STEM learning contexts.   

Simpson, A., & Maltese, A. (2017). “Failure Is a Major Component of Learning Anything”: The Role of Failure in the Development of STEM Professionals. Journal of Science Education and Technology, 26(2), 223–237. https://doi.org/10.1007/s10956-016-9674-9 

An analysis of the role failures play in the pursuit of STEM-related careers, based on interview data with professionals across STEM.  Attempts to take into account the low number of women and underrepresented minorities pursing and working in a STEM field and contribute research-based results to current conversation around incorporating failure into formal and informal educational settings and standards-based practices.  

Social Sciences 

Nachtigall, V., Serova, K., & Rummel, N. (2020). When failure fails to be productive: probing the effectiveness of productive failure for learning beyond STEM domains. Instructional Science, 48(6), 651–697. https://doi.org/10.1007/s11251-020-09525-2 

An investigation of the effectiveness of Productive Failure (PF) models on learning social science research methods via two quasi-experimental studies conducted with 10th graders. Findings did not replicate the positive results reported by studies of PF in STEM learning fields; rather, in this study, students learning social science research methods from Productive Failure did not outperform students learning from Direct Instruction.  

Problem-based Learning  

Swan, K., Vahey, P., van’t Hooft, M., Kratcoski, A., Rafanan, K., Stanford, T., Yarnall, L., & Cook, D. (2013). Problem-based Learning Across the Curriculum: Exploring the Efficacy of a Cross-curricular Application of Preparation for Future Learning. The Interdisciplinary Journal of Problem-Based Learning, 7(1), 91–. https://doi.org/10.7771/1541-5015.1307 

This paper examines the efficacy of a variant of problem-based learning, the Preparation for Future Learning (PFL) approach, to teaching and learning within the context of a cross-curricular, middle school data literacy unit called Thinking with Data (TWD). Challenging, open-ended questions, collaborative learning, and constructivist pedagogies are characteristic of both PBL and PFL. While previous studies have shown the efficacy of PFL in supporting learning in a single subject area, these findings demonstrate its efficacy in facilitating learning across disciplinary modules as well.