Exploring the Feasibility of Using Knowledge Surveys to Increase Student Knowledge, Clinical Skills and Assess Student Perceptions
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Published:
Jun 23, 2022
Keywords:
student confidence; educational assessment; nursing education; nursing students; simulation evaluation tool; Dunning-Kruger effect; End-of-Life simulation
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Abstract
This study explored the feasibility of using knowledge surveys (KSs) in a pre-licensure professional nursing program using cognitive and behavioral outcomes and illustrates how profession-specific competencies can be imbedded into a KS. This study introduces the KS as a potentially useful tool for formative and summative application in nursing education.
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Goering, M. D. (2022). Exploring the Feasibility of Using Knowledge Surveys to Increase Student Knowledge, Clinical Skills and Assess Student Perceptions. Journal of the Scholarship of Teaching and Learning, 22(2). https://doi.org/10.14434/josotl.v22i2.29489
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References
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Baumgart, S., & Hassemer, E. (2008). Online knowledge surveys as a means of library instruction assessment. In T. Valko & B. Sietz (Eds.), LOEX Conference Proceedings 2006: Moving Targets: Understanding Our Changing Landscape(s) (pp.115-119). Retrieved from https://commons.emich.edu/cgi/viewcontent.cgi?article=1024&context=loexconf2006
Bell, P., & Volckmann, D. (2011). Knowledge surveys in general chemistry: Confidence, overconfidence, and performance. Journal of Chemical Education, 88(11), 1469–1476. Retrieved from https://doi.org/10.1021/ed100328c
Bowers, N., Brandon, M., & Hill, C. D. (2005). The use of a knowledge survey as an indicator of student learning in an introductory biology course. Cell Biology Education, 4, 311-322. Retrieved from https://www.lifescied.org/doi/full/10.1187/cbe.04-11-0056
Brown, M. G. (2016). Internet and higher education blended instructional practice : A review of the empirical literature on instructors’ adoption and use of online tools in face-to-face teaching. The Internet and Higher Education, 31, 1–10. Retrieved from https://doi.org/10.1016/j.iheduc.2016.05.001
Cant, R. P., & Cooper, S. J. (2014). Simulation in the internet age: The place of web-based simulation in nursing education. An integrative review. Nurse Education Today, 34(12), 1435–1442. Retrieved from https://doi.org/10.1016/j.nedt.2014.08.001
Clauss, J., & Geedey, K. (2010). Knowledge surveys: Students ability to self-assess. Journal of the Scholarship of Teaching and Learning, 10(2), 14–24. Retrieved from https://www.researchgate.net/publication/228502606_Knowledge_surveys_Students_ability_to_self-assess
Coyne, E., Frommolt, V., Rands, H., Kain, V., & Mitchell, M. (2018). Simulation videos presented in a blended learning platform to improve Australian nursing students’ knowledge of family assessment. Nursing Education Today, 66, 96-102. Retrieved from https://doi.org/10.1016/j.nedt.2018.04.012
Cronenwett, L., Sherwood, G., Barnsteiner, J., Disch, J., Johnson, J…Warren, J. (2007). Quality and safety education for nurses. Nursing Outlook, 55(3), 122-131. Retrieved from https://doi.org/10.1016/j.outlook.2007.02.006
Davishahl, E. (2017). Knowledge surveys in engineering statics. In ASEE Annual Conference and Exposition, Conference Proceedings (Vol. 2017–June). Retrieved from https://www.semanticscholar.org/paper/Knowledge-Surveys-in-Engineering-Statics-Davishahl/82037c466adc0df61d0e2c02f8fdcb7e60874c27
Donovan, L. M., Argenbright, C. A., Mullen, L. K., & Humbert, J. L. (2018). Computer-based simulation: Effective tool or hindrance for undergraduate nursing students? Nursing Education Today, 69, 122-127. Retrieved from https://doi.org/10.1016/j.nedt.2018.07.007
Ehrlinger, J., Johnson, K., Banner, M., Dunning, D., & Kruger, J. (2008). Why the unskilled are unaware: Further explorations of (absent) self-insight among the incompetent. Organizational Behavior and Human Decision Processes, 105, 98-121. Retrieved from https://doi.org/10.1016/j.obhdp.2007.05.002
Elliot, A. C., & Woodward, W. A. (2016). IBM® SPSS® by example: A practical guide to statistical data analysis. Los Angeles: Sage.
Favazzo, L., Willford, J. D., & Watson, R. M. (2014). Correlating student knowledge and confidence using a graded knowledge survey to assess student learning in a general microbiology classroom. Journal of Microbiology & Biology Education, 15(2), 251-258. Retrieved from http://dx.doi.org/10.1128/jmbe.v15i2.693
IBM Corp. (2015). IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp.
Jarzemsky, P., McCarthy, J., & Ellis, N. (2010). Incorporating quality and safety education for nurses competencies in simulation scenario design. Nurse Education, 35(2), 90-92. Retrieved from https://journals.lww.com/nurseeducatoronline/Fulltext/2010/03000/Incorporating_Quality_and_Safety_Education_for.18.aspx
Jordan, J. (2007). The application of statistics education research in my classroom. Journal of Statistics Education, 15(2). Retrieved from https://doi.org/10.1080/10691898.2007.11889468
Karatjas, A. G. (2013). Comparing college students’ self-assessment of knowledge in organic chemistry to their actual performance. Journal of Chemical Education, 90, 1096-1099. Retrieved from http://dx.doi.org/10.1021/ed400037p
Kim, E. (2018). Effect of simulation-based emergency cardiac arrest education on nursing students' self-efficacy and critical thinking skills: Roleplay versus lecture. Nurse Education Today, 61, 258-263. Retrieved from https://doi.org/10.1016/j.nedt.2017.12.003
King, H., & Andrews, J. (2011). Geological field skills course report and future plans. Planet, 24(1), 55-61. Retrieved from https://doi.org/10.11120/plan.2011.00240055
King, P. M. & Kitchener, K. S. (2004). Reflective judgement: Theory and research on the development on the development of epistemic assumptions through adulthood. Educational Psychologist, 39(1), 5-18. Retrieved from https://doi.org/10.1207/s15326985ep3901_2
Kruger, J. & Dunning, D. (1999). Unskilled and unaware of it: How difficulties in recognizing one’s own incompetence lead to inflated self-assessments. Journal of Personality and Social Psychology, 77(6), 1121-1134. Retrieved from https://psycnet.apa.org/fulltext/1999-15054-002.html
Lee, M., Nam, K., Kim, H. (2017). Effects of simulation with problem-based learning program on metacognition, team efficacy, and learning attitude in nursing students: Nursing care with increased intracranial pressure patient. Computers, Informatics, Nursing, 35(3), 145-151. Retrieved from https://doi.org/10.1097/cin.0000000000000308
Lindsey, B. A., & Nagel, M. (2013). Assessing students’ metacognitive calibration with knowledge surveys. In AIP Conference Proceedings, 1513, 258–261. Retrieved from https://doi.org/10.1063/1.4789701
Lindsey, B. A., & Nagel, M. (2015). Do students know what they know? Exploring the accuracy of students’ self-assessments. Physics Review Special Topics Physics Education Research, 11(2). 1-11. Retrieved from https://doi.org/10.1103/PhysRevSTPER.11.020103
Luce, C., & Kirnan, J. P. (2016). Using indirect vs. direct measures in the summative assessment of student learning in higher education. Journal of the Scholarship of Teaching and Learning, 16(4), 75-91. Retrieved from https://doi.org/10.14434/josotl.v16i4.19371
Mills, B. J. (2016). Using metacognition to promote learning: IDEA paper #63. IDEA Papers. 1-9. Retrieved from https://eric.ed.gov/?id=ED573671
Nicolaysen, K. P., & Ritterbush, L. W. (2005). Critical thinking in geology and archaeology: Interpreting scanning electron microscope images of a lithic tool. Journal of Geoscience Education, 53(2), 166-172. Retrieved from https://doi.org/10.5408/1089-9995-53.2.166
Nuhfer, E. B. (1996). The place of formative evaluations in assessment and ways to reap their benefits. Journal of Geoscience Education, 44, 385-394. Retrieved from https://www.tandfonline.com/doi/abs/10.5408/1089-9995-44.4.385
Nuhfer, E., Cogan, C., Fleisher, S., Gaze, E., & Wirth, K. (2016). Random number simulations reveal how random noise affects the measurements and graphical portrayals of self-assessed competency. Numeracy, 9(1), article 4. Retrieved from http://dx.doi.org/10.5038/1936-4660.9.1.4
Nuhfer, E., & Knipp, D. (2003). The knowledge survey: A tool for all reasons. 2003 To Improve the Academy, 21, 59-78. Retrieved from https://onlinelibrary.wiley.com/doi/abs/10.1002/j.2334-4822.2003.tb00381.x
Onda, E. L. (2012). Situated cognition: Its relationship to simulation in nursing education. Clinical Simulation in Nursing, 8(7), e273-e280. Retrieved from https://doi.org/10.1016/j.ecns.2010.11.004
Paige, J. B., & Daley, B. J. (2009). Situated cognition: A learning framework to support and guide high-fidelity simulation. Clinical Simulation in Nursing, 5(3), e1-e7. Retrieved from https://doi.org/10.1016/j.ecns.2009.03.120
Pallant, J. (2013). SPSS Survival Manual: A step by step guide to data analysis using IBM SPSS. London, England: McGraw Hill.
Pearce, A. R., Bierman, P. R., Druschel, G. K., Massey, C., Rizzo, D. M…Wemple, B. C. (2010). Pitfalls and successes of developing an interdisciplinary watershed field science course. Journal of Geoscience Education, 58(3), 145–154. Retrieved from https://doi.org/10.5408/1.3544295
Price, B. A., & Randall, C. H. (2008). Assessing learning outcomes in quantitative courses: Using embedded questions for direct assessment. Journal of Education for Business, 83(5), 288–294. Retrieved from https://doi.org/10.3200/JOEB.83.5.288-294
Qalehsari, M. Q., Khaghanizadeh, M., Ebadi, A. (2017). Lifelong learning strategies in nursing: A systematic review. Electronic Physician, 9(10), 5541-5550. Retrieved from http://dx.doi.org/10.19082/5541
Qualtrics Research Core [Computer Software]. (2014). Available at https://www.qualtrics.com
Sapiano, A. B., Sammut, R., & Trapani, J. (2018). The effectiveness of virtual simulation in improving student nurses’ knowledge and performance during patient deterioration: A pre and posttest design. Nurse Education Today, 62, 128-133. Retrieved from https://doi.org/10.1016/j.nedt.2017.12.025
Webb, J. A., & Karatjas, A. G. (2018). Grade perceptions of students in chemistry coursework at all levels. Chemistry Education Research and Practice, 19, 491-499. Retrieved from https://doi.org/10.1039/c7rp00168a
Wirth, K., & Perkins, D. (2005). Knowledge surveys: An indispensable course design and assessment tool. Innovations in the Scholarship of Teaching and Learning, 1–12. Retrieved from http://serc.carleton.edu/files/garnet/knowledge_surveys_indispensabl_1313423391.pdf
Zell, E. & Krizan, Z. (2014). Do people have insight into their abilities? A metasynthesis. Perspectives on Psychological Science, 9(2), 111-125. Retrieved from https://doi.org/10.1177/1745691613518075
Baumgart, S., & Hassemer, E. (2008). Online knowledge surveys as a means of library instruction assessment. In T. Valko & B. Sietz (Eds.), LOEX Conference Proceedings 2006: Moving Targets: Understanding Our Changing Landscape(s) (pp.115-119). Retrieved from https://commons.emich.edu/cgi/viewcontent.cgi?article=1024&context=loexconf2006
Bell, P., & Volckmann, D. (2011). Knowledge surveys in general chemistry: Confidence, overconfidence, and performance. Journal of Chemical Education, 88(11), 1469–1476. Retrieved from https://doi.org/10.1021/ed100328c
Bowers, N., Brandon, M., & Hill, C. D. (2005). The use of a knowledge survey as an indicator of student learning in an introductory biology course. Cell Biology Education, 4, 311-322. Retrieved from https://www.lifescied.org/doi/full/10.1187/cbe.04-11-0056
Brown, M. G. (2016). Internet and higher education blended instructional practice : A review of the empirical literature on instructors’ adoption and use of online tools in face-to-face teaching. The Internet and Higher Education, 31, 1–10. Retrieved from https://doi.org/10.1016/j.iheduc.2016.05.001
Cant, R. P., & Cooper, S. J. (2014). Simulation in the internet age: The place of web-based simulation in nursing education. An integrative review. Nurse Education Today, 34(12), 1435–1442. Retrieved from https://doi.org/10.1016/j.nedt.2014.08.001
Clauss, J., & Geedey, K. (2010). Knowledge surveys: Students ability to self-assess. Journal of the Scholarship of Teaching and Learning, 10(2), 14–24. Retrieved from https://www.researchgate.net/publication/228502606_Knowledge_surveys_Students_ability_to_self-assess
Coyne, E., Frommolt, V., Rands, H., Kain, V., & Mitchell, M. (2018). Simulation videos presented in a blended learning platform to improve Australian nursing students’ knowledge of family assessment. Nursing Education Today, 66, 96-102. Retrieved from https://doi.org/10.1016/j.nedt.2018.04.012
Cronenwett, L., Sherwood, G., Barnsteiner, J., Disch, J., Johnson, J…Warren, J. (2007). Quality and safety education for nurses. Nursing Outlook, 55(3), 122-131. Retrieved from https://doi.org/10.1016/j.outlook.2007.02.006
Davishahl, E. (2017). Knowledge surveys in engineering statics. In ASEE Annual Conference and Exposition, Conference Proceedings (Vol. 2017–June). Retrieved from https://www.semanticscholar.org/paper/Knowledge-Surveys-in-Engineering-Statics-Davishahl/82037c466adc0df61d0e2c02f8fdcb7e60874c27
Donovan, L. M., Argenbright, C. A., Mullen, L. K., & Humbert, J. L. (2018). Computer-based simulation: Effective tool or hindrance for undergraduate nursing students? Nursing Education Today, 69, 122-127. Retrieved from https://doi.org/10.1016/j.nedt.2018.07.007
Ehrlinger, J., Johnson, K., Banner, M., Dunning, D., & Kruger, J. (2008). Why the unskilled are unaware: Further explorations of (absent) self-insight among the incompetent. Organizational Behavior and Human Decision Processes, 105, 98-121. Retrieved from https://doi.org/10.1016/j.obhdp.2007.05.002
Elliot, A. C., & Woodward, W. A. (2016). IBM® SPSS® by example: A practical guide to statistical data analysis. Los Angeles: Sage.
Favazzo, L., Willford, J. D., & Watson, R. M. (2014). Correlating student knowledge and confidence using a graded knowledge survey to assess student learning in a general microbiology classroom. Journal of Microbiology & Biology Education, 15(2), 251-258. Retrieved from http://dx.doi.org/10.1128/jmbe.v15i2.693
IBM Corp. (2015). IBM SPSS Statistics for Windows, Version 25.0. Armonk, NY: IBM Corp.
Jarzemsky, P., McCarthy, J., & Ellis, N. (2010). Incorporating quality and safety education for nurses competencies in simulation scenario design. Nurse Education, 35(2), 90-92. Retrieved from https://journals.lww.com/nurseeducatoronline/Fulltext/2010/03000/Incorporating_Quality_and_Safety_Education_for.18.aspx
Jordan, J. (2007). The application of statistics education research in my classroom. Journal of Statistics Education, 15(2). Retrieved from https://doi.org/10.1080/10691898.2007.11889468
Karatjas, A. G. (2013). Comparing college students’ self-assessment of knowledge in organic chemistry to their actual performance. Journal of Chemical Education, 90, 1096-1099. Retrieved from http://dx.doi.org/10.1021/ed400037p
Kim, E. (2018). Effect of simulation-based emergency cardiac arrest education on nursing students' self-efficacy and critical thinking skills: Roleplay versus lecture. Nurse Education Today, 61, 258-263. Retrieved from https://doi.org/10.1016/j.nedt.2017.12.003
King, H., & Andrews, J. (2011). Geological field skills course report and future plans. Planet, 24(1), 55-61. Retrieved from https://doi.org/10.11120/plan.2011.00240055
King, P. M. & Kitchener, K. S. (2004). Reflective judgement: Theory and research on the development on the development of epistemic assumptions through adulthood. Educational Psychologist, 39(1), 5-18. Retrieved from https://doi.org/10.1207/s15326985ep3901_2
Kruger, J. & Dunning, D. (1999). Unskilled and unaware of it: How difficulties in recognizing one’s own incompetence lead to inflated self-assessments. Journal of Personality and Social Psychology, 77(6), 1121-1134. Retrieved from https://psycnet.apa.org/fulltext/1999-15054-002.html
Lee, M., Nam, K., Kim, H. (2017). Effects of simulation with problem-based learning program on metacognition, team efficacy, and learning attitude in nursing students: Nursing care with increased intracranial pressure patient. Computers, Informatics, Nursing, 35(3), 145-151. Retrieved from https://doi.org/10.1097/cin.0000000000000308
Lindsey, B. A., & Nagel, M. (2013). Assessing students’ metacognitive calibration with knowledge surveys. In AIP Conference Proceedings, 1513, 258–261. Retrieved from https://doi.org/10.1063/1.4789701
Lindsey, B. A., & Nagel, M. (2015). Do students know what they know? Exploring the accuracy of students’ self-assessments. Physics Review Special Topics Physics Education Research, 11(2). 1-11. Retrieved from https://doi.org/10.1103/PhysRevSTPER.11.020103
Luce, C., & Kirnan, J. P. (2016). Using indirect vs. direct measures in the summative assessment of student learning in higher education. Journal of the Scholarship of Teaching and Learning, 16(4), 75-91. Retrieved from https://doi.org/10.14434/josotl.v16i4.19371
Mills, B. J. (2016). Using metacognition to promote learning: IDEA paper #63. IDEA Papers. 1-9. Retrieved from https://eric.ed.gov/?id=ED573671
Nicolaysen, K. P., & Ritterbush, L. W. (2005). Critical thinking in geology and archaeology: Interpreting scanning electron microscope images of a lithic tool. Journal of Geoscience Education, 53(2), 166-172. Retrieved from https://doi.org/10.5408/1089-9995-53.2.166
Nuhfer, E. B. (1996). The place of formative evaluations in assessment and ways to reap their benefits. Journal of Geoscience Education, 44, 385-394. Retrieved from https://www.tandfonline.com/doi/abs/10.5408/1089-9995-44.4.385
Nuhfer, E., Cogan, C., Fleisher, S., Gaze, E., & Wirth, K. (2016). Random number simulations reveal how random noise affects the measurements and graphical portrayals of self-assessed competency. Numeracy, 9(1), article 4. Retrieved from http://dx.doi.org/10.5038/1936-4660.9.1.4
Nuhfer, E., & Knipp, D. (2003). The knowledge survey: A tool for all reasons. 2003 To Improve the Academy, 21, 59-78. Retrieved from https://onlinelibrary.wiley.com/doi/abs/10.1002/j.2334-4822.2003.tb00381.x
Onda, E. L. (2012). Situated cognition: Its relationship to simulation in nursing education. Clinical Simulation in Nursing, 8(7), e273-e280. Retrieved from https://doi.org/10.1016/j.ecns.2010.11.004
Paige, J. B., & Daley, B. J. (2009). Situated cognition: A learning framework to support and guide high-fidelity simulation. Clinical Simulation in Nursing, 5(3), e1-e7. Retrieved from https://doi.org/10.1016/j.ecns.2009.03.120
Pallant, J. (2013). SPSS Survival Manual: A step by step guide to data analysis using IBM SPSS. London, England: McGraw Hill.
Pearce, A. R., Bierman, P. R., Druschel, G. K., Massey, C., Rizzo, D. M…Wemple, B. C. (2010). Pitfalls and successes of developing an interdisciplinary watershed field science course. Journal of Geoscience Education, 58(3), 145–154. Retrieved from https://doi.org/10.5408/1.3544295
Price, B. A., & Randall, C. H. (2008). Assessing learning outcomes in quantitative courses: Using embedded questions for direct assessment. Journal of Education for Business, 83(5), 288–294. Retrieved from https://doi.org/10.3200/JOEB.83.5.288-294
Qalehsari, M. Q., Khaghanizadeh, M., Ebadi, A. (2017). Lifelong learning strategies in nursing: A systematic review. Electronic Physician, 9(10), 5541-5550. Retrieved from http://dx.doi.org/10.19082/5541
Qualtrics Research Core [Computer Software]. (2014). Available at https://www.qualtrics.com
Sapiano, A. B., Sammut, R., & Trapani, J. (2018). The effectiveness of virtual simulation in improving student nurses’ knowledge and performance during patient deterioration: A pre and posttest design. Nurse Education Today, 62, 128-133. Retrieved from https://doi.org/10.1016/j.nedt.2017.12.025
Webb, J. A., & Karatjas, A. G. (2018). Grade perceptions of students in chemistry coursework at all levels. Chemistry Education Research and Practice, 19, 491-499. Retrieved from https://doi.org/10.1039/c7rp00168a
Wirth, K., & Perkins, D. (2005). Knowledge surveys: An indispensable course design and assessment tool. Innovations in the Scholarship of Teaching and Learning, 1–12. Retrieved from http://serc.carleton.edu/files/garnet/knowledge_surveys_indispensabl_1313423391.pdf
Zell, E. & Krizan, Z. (2014). Do people have insight into their abilities? A metasynthesis. Perspectives on Psychological Science, 9(2), 111-125. Retrieved from https://doi.org/10.1177/1745691613518075