Does smartphone-assisted student feedback affect teachers’ teaching quality?

References

• Balch, R. T. (2012). The validation of a student survey on teacher practice. Nashville, TN: Vanderbilt University.
   Google Scholar
• Bell, L. M., & Aldridge, J. M. (2014). Investigating the use of student perception data for teacher reflection and classroom improvement. Learning Environment Research, 17, 371–388.
   Google Scholar
• Bijlsma, H. J. E. (2016). Gathering feedback by means of student perceptions. A systematic review of student perception questionnaires ( Unpublished Master’s thesis). University of Groningen, Groningen.
   Google Scholar
• Black, P., & Wiliam, W. (2006). Assessment and classroom learning. Assessment in Education: Principles, Policy and Practices, 5, 7–74.
   Google Scholar
• Bron, R., Endedijk, M. D., Van Veelen, R., & Veldkamp, B. P. (2018). The joint influence of intra- and inter-team learning processes on team performance: A constructive or destructive combination. Vocations and Learning, 1–26. https://doi.org/10.1007/s12186-018-9197-z
   Web of Science ®Google Scholar
• Cantrell, S., & Kane, T. J. (2013). Ensuring fair and reliable measures of effective teaching: Culminating findings from the MET Project’s three-year study. Seattle, WA: Bill & Melinda Gates Foundation.
   Google Scholar
• Cook-Sather, A. (2002). Authorizing students’ perspectives: Toward trust, dialoque, and change in education. Educational Researcher, 31(4), 3–14. doi:10.3102/0013189X031004003
   Google Scholar
• Cook-Sather, A. (2007). What would happen if we treated students as those with opinions that matter? The benefits to principals and teachers of supporting youth engagement in school. NASSP Bulletin, 91(4), 343–362. doi:10.1177/0192636507309872
   Google Scholar
• COTAN. (2010). Beoordelingssysteem voor de kwaliteit van tests. Geheel herziene versie [Quality of tests evaluation system. Completely revised version]. Utrecht: NIP.
   Google Scholar
• Creemers, B. M. P. (1994). The effective classroom. London: Cassell.
   Google Scholar
• Day, C., Sammons, P., & Kington, A. (2008). Effective classroom practice (ECP): A mixed-method study of influences and outcomes. Nottingham: School of Education, University of Nottingham.
   Google Scholar
• De Vocht, A. (2016). Basisboek SPSS 24 [Handbook SPSS 24]. Utrecht: Bijleveld Uitgeverij.
   Google Scholar
• Den Brok, P., Brekelmans, M., & Wubbels, T. (2007). Multilevel issues in research using students’ perceptions of learning environments: The case of the Questionnaire on Teacher Interaction. Learning Environment Research, 9, 199–213.
   Google Scholar
• Driessen, E., Van Tartwijk, J., & Dornan, T. (2008). The self-critical doctor: Helping students become more reflective. BMJ, 336, 827–830.
   PubMed Web of Science ®Google Scholar
• Drijvers, P. (2015). Denken over wiskunde, onderwijs en ICT. Rede uit gesproken op 21 mei 2015 aan: de Universiteit Utrecht [Thinking about mathematics, education and ICT. Inauguration speech, 21 May 2015 at the University of Utrecht].
   Google Scholar
• Dunn, T. J., Baguley, T., & Brunsden, V. (2013). From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation. British Journal of Psychology, 105, 399–412. doi:10.1111/bjop.12046
   PubMed Web of Science ®Google Scholar
• Ericsson, K. A. (2006). The influence of experience and deliberate practice on the development of superior expert performance. In K. A. Ericsson (Ed.), The Cambridge handbook of expertise and expert performance (Vol. 38, pp. 685–705). New York, NY: Cambridge University Press.
   Google Scholar
• Ertmer, P. A., & Newby, T. J. (1996). The expert learner: Stragic, self-regulated and reflective. Instructional Sciences, 24, 1–24.
   Web of Science ®Google Scholar
• Fauth, B., Decristan, J., Rieser, S., Klieme, E., & Büttner, G. (2014). Students ratings of teaching quality in primary school: Dimensions and prediction of student outcomes. Learning and Instruction, 29, 1–9.
   Web of Science ®Google Scholar
• Ferguson, R. F. (2012). Can student surveys measure teaching quality? Phi Delta Kappan, 94(3), 24–28.
   Web of Science ®Google Scholar
• Field, A. P. (2013). Discovering statistics using IBM SPSS statistics: And sex and drugs and rock ‘n’ roll. Los Angeles, CA: Sage.
   Google Scholar
• Fogg, B. J. (2009). A behavioural model for persuasive design. Stanford University: Persuasive Technology Lab.
   Google Scholar
• Fraenkel, J. R., Hyun, H. H., & Wallen, N. E. (2012). How to design and evaluate research in education. New York, NY: Mcgraw-Hill Education.
   Google Scholar
• Fraser, B. J. (1998). Science learning environments: assessment, effects and determinants. In B. J. Fraser & K. G. Tobin (Eds.), International handbook of science education (pp. 527–564). London: Kluwer Academic Publishers.
   Google Scholar
• Fraser, B. J. (2007). Classroom learning environments. In S. K. Abell & N. G. Lederman (Eds.), Handbook of research in science education (pp. 103–124). Mahwah, NJ: Lawrence Erlbaum.
   Google Scholar
• Fresko, B., & Nasser, F. (2001). Interpreting student ratings: consultation, instructional modification, and attitudes towards course evaluation. Studies in Educational Evaluation, 27, 291–305.
   Google Scholar
• Gaertner, H. (2014). Effects of student feedback as a method of self-evaluating the quality of teaching. Studies in Educational Evaluation, 42, 91–99.
   Web of Science ®Google Scholar
• Hattie, J. (2008). Visible learning. A synthesis over 800 meta-analyses relating to achievement. Abingdon: Routledge.
   Google Scholar
• Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77, 81–112. doi:10.3102/003465430298487
   Web of Science ®Google Scholar
• Hiebert, J., & Grouws, D. A. (2007). The effects of classroom mathematics teaching on students’ learning. In F. K. Lester (Ed.), Second handbook of research on mathematics teaching and learning (pp. 371–404). Charlotte, NC: Information Age.
   Google Scholar
• Hill, H. C., Charalambous, C. Y., & Kraft, M. A. (2012). When rater reliability is not enough: Teacher observation systems and a case for the generalizability study. Educational Researcher, 41(2), 56–64.
   Web of Science ®Google Scholar
• Hoban, G. F. (2004). Enhancing action learning with student feedback. Action Learning: Research and Practice, 1, 203–218.
   Google Scholar
• Hoban, G. F., & Hastings, G. (2006). Developing different forms of student feedback to promote teacher reflection: A 10-year collaboration. Teaching and Teacher Education, 22, 1006–1019.
   Web of Science ®Google Scholar
• Hollingsworth, J., & Ybarra, S. (2015). Explicit direct instruction (ED): The power of the well-crafted, well-taught lesson. Thousand Oaks, CA: Corwin Press.
   Google Scholar
• Ilgen, D. R., Fisher, C. D., & Taylor, M. S. (1979). Consequences of individual feedback on behavior in organizations. Journal of Applied Psychology, 64, 349–371. doi:10.1037/0021-9010.64.4.349
   Web of Science ®Google Scholar
• Kane, T. J., & Staiger, D. O. (2012). Gathering feedback for teaching: Combining high-quality observations with student surveys and achievement gains. Research paper. MET project. Seattle, WA: Bill & Melinda Gates Foundation.
   Google Scholar
• Kember, D., Leung, D. Y. P., Jones, A., Yuen Loke, A., McKay, J., Sinclair, K., … Yeung, E. (2010). Development of a questionnaire to measure the level of reflective Thinking. Assessment & Evaluation in Higher Education, 25(4), 380–395.
   Google Scholar
• Kluger, A. N., & DeNisi, A. (1996). The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory. Psychological Bulletin, 119, 254–284.
   Web of Science ®Google Scholar
• Könings, K. D., Van Berlo, J., Koopmans, R., Hoogland, H., Spanjers, I. A. E., Ten Haaf, J. A., & Van Merriënboer, J. J. G. (2016). Using a smartphone app and coaching group sessions to promote residents’ reflection in the workplace. Academic Medicine, 91, 365–370.
   PubMed Web of Science ®Google Scholar
• Lasagabaster, D., & Sierrra, J. M. (2011). Classroom observation: Desirable conditions established by teachers. European Journal of Teacher Education, 34, 449–463.
   Web of Science ®Google Scholar
• Leatherdale, S. T., Cameron, R., Brown, K. S., & McDonald, P. W. (2005). Senior student smoking at school, student characteristics, and smoking onset among junior students: A multilevel analysis. Prev. Med., 40, 853–859.
   PubMed Web of Science ®Google Scholar
• Levin, J. A., & Datnow, A. (2012). The principal role in data-driven decision making: Using case-study data to develop multi-mediator models of educational reform. School Effectiveness and School Improvement, 23, 179–202.
   Web of Science ®Google Scholar
• Lincoln, Y. S. (1995). In search of student voices. Theory into Practice, 34, 88–93.
   Web of Science ®Google Scholar
• MacNell, L., Driscoll, A., & Hunt, A. N. (2015). What’s in a name: Exposing gender bias in student ratings of teachers. Innovative Higher Education, 40, 291–303.
   Web of Science ®Google Scholar
• Marzano, R. J. (2003). What works in schools. Translating research into action. Alexandria, VA: ASCD.
   Google Scholar
• Maulana, R., Helms-Lorenz, M., & Van de Grift, W. J. C. M. (2015). Development and evaluation of a questionnaire measuring pre-service teachers’ teaching behaviour: A Rasch modelling approach. School Effectiveness and School Improvement, 26, 169–194. doi:10.1080/09243453.2014.939198
   Web of Science ®Google Scholar
• Miller, M. T. (1971). Instructors’ attitudes toward, and their use of, student ratings of teachers. Journal of Educational Psychology, 62, 235–239.
   Web of Science ®Google Scholar
• Moorman, R. H., & Podsakoff, P. M. (1992). A meta-analytic review and empirical test of the potential confounding effects of social desirability response sets in organizational behaviour research. Journal of Occupational and Organizational Psychology, 65, 131–149.
   Web of Science ®Google Scholar
• Muijs, D. (2006). Measuring teacher effectiveness: Some methodological reflections. Educational Research and Evaluation, 12, 53–75.
   Google Scholar
• Muijs, D., Kyriakides, L., Van der Werf, G., Creemers, B. M. P., Timperley, H., & Earl, L. (2014). State of the art – Teacher effectiveness and professional learning. School Effectiveness and School Improvement, 25, 231–256.
   Web of Science ®Google Scholar
• Oinas-Kukkonen, H., & Harjumaa, M. (2009). Persuasive systems design: Key issues, process model, and system features. Communications of the Association for Information Systems, 24, 485–500.
   Google Scholar
• Pambookian, H. S. (1972). The effect of feedback from students to college instructors on their teaching behavior ( Unpublished doctoral dissertation). University of Michigan.
   Google Scholar
• Pambookian, H. S. (1976). Discrepancy between instructor and student evaluations of instruction: Effect on instructor. Instructional Sciences, 5, 63–75.
   Web of Science ®Google Scholar
• Peterson, K. D., Wahlquist, C., & Bone, K. (2000). Student surveys for school teacher evaluation. Journal of Personnel Evaluation in Education, 14, 135–153.
   Google Scholar
• Peugh, J. L. (2010). A practical guide to multilevel modeling. Journal of School Psychology, 48, 85–112. doi:10.1016/j.jsp.2009.09.002
   PubMed Web of Science ®Google Scholar
• Pianta, R. C., & Hamre, B. K. (2006). Conceptualization, measurement, and improvement of classroom processes: Standardized observation can leverage capacity. Educational Researcher, 38, 109–119.
   Google Scholar
• Quaglia, R., & Corso, M. (2017). Lef om te luisteren. Met leerlingen werken aan de kwaliteit van onderwijs [Student voice: The instrument of change]. Huizen: Pica.
   Google Scholar
• Reynolds, D., Sammons, P., De Fraine, B., Van Damme, J., Towsend, T., Teddlie, C., & Stringfield, S. (2014). Educational effectiveness research (EER): A state-of-the-art review. School Effectiveness and School Improvement, 25, 197–230.
   Web of Science ®Google Scholar
• Roche, L. A., & Marsh, H. W. (2000). Multiple dimensions of university teacher self-concept: Construct validation and the influence of students’ evaluations of teaching. Instructional Sciences, 28, 439–468.
   Web of Science ®Google Scholar
• Rosenshine, B. (1995). Advances in research on instruction. Journal of Educational Research, 88, 262–268.
   Web of Science ®Google Scholar
• Sammons, P., Hillman, J., & Mortimore, P. (1995). Key characteristics of effective schools: A review of school effectiveness research. London: Institute of Education.
   Google Scholar
• Santos, J. R. A. (1999). Cronbach’s alpha: A tool for assessing the reliability of scales. Tools of the Trade (Texas A&M University), 37(2). Retrieved from https://joe.org/joe/1999april/tt3.php 
   Google Scholar
• Sawada, D., Piburn, M. D., Judson, E., Turley, J., Falconer, K., Benford, R., & Bloom, I. (2002). Measuring reform practices in science and mathematics classrooms: The reformed teaching observation protocol. Measuring Reform Practices, 102, 245–253.
   Google Scholar
• Schildkamp, K., & Lai, M. K. (2013). Conclusions and a data use framework. In K. Schildkamp & M. K. Lai (Eds.), Data-based decision making in education: Challenges and opportunities (pp. 177–191). Dordrecht: Springer.
   Google Scholar
• Seifert, T. (2018, March). Smartphone implementation from lecturers, teachers, students and pupils’ perspectives. Paper presented at the SITE conference, Washington, DC.
   Google Scholar
• Shute, V. J. (2008). Focus on formative feedback. Review of Educational Research, 78, 153–189.
   Web of Science ®Google Scholar
• Sijtsma, K. (2009). Over misverstanden rond Cronbach’s alpha en de wenselijkheid van alternatieven [About misunderstandings of Cronbach's alpha and the desirability of alternatives]. De Psycholoog [The Psychologist], 44, 561–567.
   Google Scholar
• Sluijsmans, D., & Kneyber, R. (2016). Toetsrevolutie. Naar een feedbackcultuur in het voortgezet onderwijs [Tests revolution. Towards a feedback culture in secondary education]. Leiden: Phronese.
   Google Scholar
• Snijders, T., & Bosker, B. (1999). Multilevel analysis: An introduction to basic and advanced multilevel modeling. London: Sage.
   Google Scholar
• Timmers, C. F., & Veldkamp, B. P. (2011). Attention paid to feedback provided by a computer-based assessment for learning on information literacy. Computers in Education, 56, 923–930.
   Web of Science ®Google Scholar
• Tuckman, B. W., & Olivier, W. F. (1968). Effectiveness of feedback to teachers as a function of source. Journal of Educational Psychology, 59, 297–301.
   PubMed Web of Science ®Google Scholar
• Van de Grift, W. J. C. M. (2007). Quality of teaching in four European countries: A review of the literature and application of an assessment instrument. Educational Research and Evaluation, 49, 127–152.
   Google Scholar
• Van de Grift, W. J. C. M. (2010). Ontwikkeling in de beroepsvaardigheden van leraren. Rede uitgesproken op 23 maart 2010: Rijksuniversiteit Groningen [Development in the professional skills of teachers. Inauguration speech, 23 March 2010: University of Groningen].
   Google Scholar
• Van der Lans, R. M. (2017). Teacher evaluation through observation ( Unpublished doctoral dissertation). University of Groningen.
   Google Scholar
• Van der Lans, R. M., Van de Grift, W. J. C. M., & Van Veen, K. (2016). Developing a teacher evaluation instrument to provide formative feedback using students’ ratings of teaching acts. Educational Measurement: Issue and Practice, 34(3), 18–27.
   Web of Science ®Google Scholar
• Van der Scheer, E. A., Bijlsma, H. J. E., & Glas, C. (in press). Validity and reliability of student perceptions of teaching quality in primary education. School Effectiveness and School Improvement.
   Web of Science ®Google Scholar
• Van der Scheer, E. A., & Visscher, A. J. (2017). Effects of a data-based decision-making intervention for teachers on students’ mathematical achievement. Journal of Teacher Education, 1–14. doi:10.1177/0022487117704170
   Web of Science ®Google Scholar
• Visscher, A. J. (2015). On the relevance of data-based decision-making in education. Inaugural speech, University of Groningen.
   Google Scholar
• Voerman, L., Meijer, P. C., Korthagen, F. A. J., & Simons, R. J. (2012). Types and frequencies of feedback interventions in classroom interaction in secondary education. Teaching and Teacher Education, 28, 1107–1115.
   Web of Science ®Google Scholar
• Weisberg, H. F. (1992). Central tendency and variability. Sage University paper series on Quantitative Applications in the Social Sciences. Newbury Park, CA: Sage.
   Google Scholar
• Wohlstetter, P., Datnow, A., & Park, V. (2008). Creating a system for data-driven decision-making: Applying the principal-agent framework. School Effectiveness and School Improvement, 19, 239–259.
   Web of Science ®Google Scholar