Abstract
Audience response systems (ARS) allow lecturers to run quizzes in large classes by handing to technology the time-consuming tasks of collecting and aggregating students’ answers. ARSs provide immediate feedback to lecturers and students alike. The first commercial ARSs emerged in the 1990s in form of clickers, i.e., transmitters equipped with a number of buttons, which impose restrictions on possible questions – most often, only multiple choice and numerical answers are possible.
Starting from the early 2010s, the ubiquity of smartphones, laptops, and tablet computers paved the way for web-based ARSs which, while running on technology that provides more means for input and a graphical display, still have much in common with their precursors: Even though more types of questions besides multiple choice are supported, the full capability of web-based technology is still not fully exploited. Furthermore, they also do not adapt to a student’s needs and knowledge, and often restrict quizzes to two phases: Answering a question and viewing the results.
This article first examines the current state of web-based ARSs: Question types found in current ARSs are identified and their support in a variety of ARSs is examined. Afterwards, three axes on which ARSs should advance in the future are introduced: Means of input, adaption to students, and support for multiple phases. Each axis is illustrated with concrete examples of quizzes.
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References
Azevedo, R., Hadwin, A.F.: Scaffolding self-regulated learning and metacognition-implications for the design of computer-based scaffolds. Instr. Sci. 33(5), 367–379 (2005)
Brusilovsky, P., Millán, E.: User models for adaptive hypermedia and adaptive educational systems. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web. LNCS, vol. 4321, pp. 3–53. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-72079-9_1
Bryfczynski, S.P., et al.: uRespond: iPad as interactive, personal response system. J. Chem. Educ. 91(3), 357–363 (2014)
Caldwell, J.E.: Clickers in the large classroom: current research and best-practice tips. CBE-Life Sci. Educ. 6(1), 9–20 (2007)
Cooper, M.M., Grove, N., Underwood, S.M., Klymkowsky, M.W.: Lost in Lewis structures: an investigation of student difficulties in developing representational competence. J. Chem. Educ. 87(8), 869–874 (2010)
Crouch, C.H., Mazur, E.: Peer instruction: ten years of experience and results. Am. J. Phys. 69(9), 970–977 (2001)
González-Tato, J., Llamas-Nistal, M., Caeiro-Rodríguez, M., Mikic-Fonte, F.A., et al.: Web-based audience response system using the educational platform called BeA. J. Res. Pract. Inf. Technol. 45(3/4), 251 (2013)
Gross, M.: Collective peer evaluation of quiz answers in large classes through pairwise matching, Institute of Informatics, Ludwig Maximilian University of Munich. Bachelor thesis (2017)
Grüner, G.: Die didaktische Reduktion als Kernstück der Didaktik. Die Deutsche Schule 59(7/8), 414–430 (1967)
Haladyna, T.M.: Writing Test Items to Evaluate Higher Order Thinking. ERIC, New York (1997)
Hattie, J., Timperley, H.: The power of feedback. Rev. Educ. Res. 77(1), 81–112 (2007)
Hauswirth, M.: Informa: an extensible framework for group response systems. In: Bertino, E., Joshi, J.B.D. (eds.) CollaborateCom 2008. LNICST, vol. 10, pp. 271–286. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-03354-4_21
Hauswirth, M.: Models and clickers for teaching computer science. In: 7th Educators’ Symposium@ MODELS (2011)
Hauswirth, M., Adamoli, A.: Teaching java programming with the informa clicker system. Sci. Comput. Program. 78(5), 499–520 (2013)
Hunsu, N.J., Adesope, O., Bayly, D.J.: A meta-analysis of the effects of audience response systems (clicker-based technologies) on cognition and affect. Comput. Educ. 94, 102–119 (2016)
Hwang, G.J.: Definition, framework and research issues of smart learning environment - a context-aware ubiquitous learning perspective. Smart Learn. Environ. 1(1), 4 (2014)
Imazeki, J.: Bring-your-own-device: turning cell phones into forces for good. J. Econ. Educ. 45(3), 240–250 (2014)
Jensen, J.L., McDaniel, M.A., Woodard, S.M., Kummer, T.A.: Teaching to the test or testing to teach: exams requiring higher order thinking skills encourage greater conceptual understanding. Educ. Psychol. Rev. 26(2), 307–329 (2014)
Jumaat, N.F., Tasir, Z.: Instructional scaffolding in online learning environment: a meta-analysis. In: 2014 International Conference on Teaching and Learning in Computing and Engineering, pp. 74–77. IEEE (2014)
Kay, R.H., LeSage, A.: Examining the benefits and challenges of using audience response systems: a review of the literature. Comput. Educ. 53(3), 819–827 (2009)
Kulik, J.A., Kulik, C.L.C.: Timing of feedback and verbal learning. Rev. Educ. Res. 58(1), 79–97 (1988)
Mader, S., Bry, F.: Phased classroom instruction: a case study on teaching programming languages. In: Proceedings of the 11th International Conference on Computer Supported Education, CSEDU, vol. 1, pp. 241–251. SciTePress (2019)
Maheady, L., Mallette, B., Harper, G.F., Sacca, K.: Heads together: a peer-mediated option for improving the academic achievement of heterogeneous learning groups. Remedial Spec. Educ. 12(2), 25–33 (1991)
Martyn, M.: Clickers in the classroom: an active learning approach. Educ. Q. 30(2), 71 (2007)
McLoone, S., Brennan, C.: A smartphone-based student response system for obtaining high quality real-time feedback-evaluated in an engineering mathematics classroom: National university of ireland maynooth. Thinking Assessment in Science and Mathematics, p. 148 (2013)
Roselli, R.J., Brophy, S.P.: Experiences with formative assessment in engineering classrooms. J. Eng. Educ. 95(4), 325–333 (2006)
Schön, D., Klinger, M., Kopf, S., Weigold, T., Effelsberg, W.: Customizable learning scenarios for students’ mobile devices in large university lectures: a next generation audience response system. In: Zvacek, S., Restivo, M.T., Uhomoibhi, J., Helfert, M. (eds.) CSEDU 2015. CCIS, vol. 583, pp. 189–207. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-29585-5_11
Stanger-Hall, K.F.: Multiple-choice exams: an obstacle for higher-level thinking in introductory science classes. CBE-Life Sci. Educ. 11(3), 294–306 (2012)
Staudacher, K., Mader, S., Bry, F.: Automated scaffolding and feedback for proof construction: a case study. In: Proceedings of the 18th European Conference on e-Learning (ECEL 2019). ACPI (2019, to appear)
Van Merriënboer, J.J., Kirschner, P.A., Kester, L.: Taking the load off a learner’s mind: instructional design for complex learning. Educ. Psychol. 38(1), 5–13 (2003)
White, E.M.: Assessing higher-order thinking and communication skills in college graduates through writing. J. Gen. Educ. 42(2), 105–122 (1993)
Wood, D., Bruner, J.S., Ross, G.: The role of tutoring in problem solving. J. Child Psychol. Psychiatry 17(2), 89–100 (1976)
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Mader, S., Bry, F. (2019). Audience Response Systems Reimagined. In: Herzog, M., Kubincová, Z., Han, P., Temperini, M. (eds) Advances in Web-Based Learning – ICWL 2019. ICWL 2019. Lecture Notes in Computer Science(), vol 11841. Springer, Cham. https://doi.org/10.1007/978-3-030-35758-0_19
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