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Beyond descriptions and good practices. Empirical effects of active learning environments on political science students’ learning outcomes. Academic teaching in political science has evolved from teacher-centered towards student-centered teaching. This trend is accompanied by the creation of student-activating learning environments (Krain et al. 2015; Lantis et al. 2010; Ishiyama et al. 2016) by means of - inter alia – debates, roll plays, simulations (e.g. Asal & Blake 2006; Elias 2014), (community) service learning (Freeland 2009), technology based learning such as online forums, social media, wikis and audience response systems (Parmentier 2013), media-based learning using novels, films, music and podcasts (Leckrone 2013) and problem based learning (Krain 2010). Advocates of active learning environments make a number of claims. Active learning is argued to have a positive effect on study results (Raymond and Usherwood 2013), on learning regarding the self (Druckman & Ebner 2013), on skills such as critical thinking, negotiating, presenting and public speaking (Schnurr et al. 2014), on affective learning in terms of empathy and appreciation for the complexity of the real world (Druckman & Ebner 2013), on motivation (Raymond and Usherwood 2013) and on different types of interest (Schnurr et al. 2014). The political science research community has increasingly devoted attention to how to teach the discipline. Global and regional professional organizations (such as IPSA and ECPR) and more thematic scholarly communities (such UACES and EUSA for EU studies) have reserved slots for sections and panels in their conferences and have created interest sections or standing groups on teaching and learning. More in particular this proposal connects well with the initiatives of the ECPR Standing Group on Teaching and Learning Politics. In addition, journals such as European Political Science, International Studies Perspectives and PS Political Science and Politics now include symposia, round-tables and regular research articles on teaching innovations. In addition, several edited volumes discussing good practices have been published (Ishiyama et al. 2016; Lightfoot & Gormley-Heenan 2012; Simon & Pleschova 2012). There is even a specifically dedicated journal (Journal of Political Science Education) on the subject. Finally, blogs such as Active Learning in Political Science and websites such as the Political Studies Association IPED database have been created to share good practices and promote innovative (active) teaching methods. However, in contrast with the rhetoric and the many claims in the current literature, substantial empirical evidence on the effects of active learning environments on student learning outcomes is still limited (Baranowski & Weir 2015). Most of these claims have not been systematically tested. For instance, proof of simulations’ effectiveness in any of the instances described above is rather anecdotal and often methodologically poor, and sometimes even contradictory (Chin et al 2009; Hofstede et al. 2010). Most studies examined only cross-sectional student feedback (self-reporting; Shellman & Turan 2006) or relations between participation in simulations and study results (Raymond 2010). In addition and more generally, the literature has quite a large US bias as most studies to date have been conducted there (Ishiyama 2013). Only more recently have scholars moved beyond descriptive studies (Blair 2016; Duchatelet et al. 2017). Overall, however, the effects of active learning environments on student learning outcomes remain understudied. We see two reasons why the effects of active learning environments in political science curricula have not yet been studied systematically. First, political science teaching has not yet attracted attention by educational researchers who are (also) experts in effect studies. Secondly, this also means that studies on the effect of active learning tools in political science have largely been the work of political scientists, who might be very knowledgeable in studying effects, but do not necessarily speak to the educational literature. It is the aim of this workshop to build bridges and combine the expertise of political science and educational sciences in order to test the effects of active learning in political science curricula. This workshop intends to bring systematic empirical evidence of the effect of active learning tools to the discipline of political science, inspired by and drawing from educational research. Educational research usually distinguishes between three general learning activities and resulting learning outcomes, which have only been implicitly acknowledged within political science (Duchatelet et al. 2017): cognitive, affective and regulative (Vermunt and Vermetten, 2004). Cognitive learning outcomes are results of those thinking activities that directly lead to learning in terms of knowledge, understanding, skills and so on (Vermunt and Vermetten, 2004). Within the research field of political science teaching and learning, such learning outcomes are mostly specified as better understanding of theoretical concepts and/or theories (e.g. Andonova and Mendoza-Castro, 2008; Bridge and Radford, 2014; Elias, 2014), increased knowledge (e.g. Obendorf and Randerson, 2013; Zaino and Mulligan, 2009) and developed skills such as communicating (e.g. DiCicco, 2014; Elias, 2014). Affective learning outcomes are the results of feelings that arise during learning and that create an emotional state that may positively, neutrally or negatively affect the learning process (Vermunt and Vermetten, 2004). Research on the use of active learning within political science mostly defines these outcomes as interest (e.g. Bridge and Radford, 2014; Zaino and Mulligan, 2009) or motivation (e.g. DiCicco, 2014; Jones and Bursens, 2015). Both cognitive and affective activities are directed by regulating activities that indirectly lead to learning results, such as the ability to monitor and, when needed, to adjust the learning process (Vermunt and Vermetten, 2004). This process of learning has thus far not directly been studied in the field of political science teaching and learning. However, studies on simulations for instance, often report about the importance of reflective assignments and debriefing sessions (e.g. Elias, 2014; Usherwood, 2013), which can be seen as activities that stimulate students to use their reflective skills and therefore foster regulative learning outcomes (Vermunt and Vermetten, 2004). In addition, all three outcomes have shown to be positively related to academic performance, although they may vary based on students’ gender, prior knowledge, prior education or prior results (e.g. Richardson et al. 2012; Robbins et al. 2004). Translating this discussion into research questions, this workshop seeks to address the following. Do active learning environments enhance political science students’ learning outcomes? Does the introduction of active learning in political science curricula make a difference for cognitive, affective and/or regulative learning outcomes? Which conditions make active learning tools more or less effective? What are the inhibiting and stimulating factors? Are there differential effects according to specific student attributes such as gender, prior knowledge, prior education or prior results? Political science scholars also teach political science courses. Many of them have experimented with innovative learning tools and some even have collected data on study results and other student characteristics and achievements. This workshop aims to activate these data or to encourage scholars to systematically collect and analyze data in order to substantiate the claims that have been made in a rather unsatisfactory way thus far. By doing this, the workshop promises to deliver innovative insights in political science teaching. Discussing research at the crossroads of political science and educational science entails clear benefits for the former, as political scientists have not yet systematically used insights from research on learning effects of students. Most political science publications on active learning discuss how to implement the tool in class but often fall short of providing evidence of the effects on student outcomes such as increased interest and performance. Combining the two disciplines will enable political science to benefit from state of the art educational science measurement tools and to test the claims made by the proponents of active learning tools. Finally, as a spin off, the workshop will deliver practical innovation. The content of the contributions will not only result in scientific findings regarding the effects of learning environments, but in addition the generated knowledge about whether and under which conditions active learning tools have effects, will enable academic teachers to optimize their learning environments as well. References Andonova, L.B. and Mendoza-Castro, R. (2008). The next climate treaty? Pedagogical and policy lessons of classroom negotiations. International Studies Perspectives, 9(3), 331-347. Asal, V., & Blake, E. (2006). Creating simulations for political science education. Journal of Political Science Education, 2(1), 1-18. Belova, N., Eilks, I., & Feierabend, T. (2015). The evaluation of role-playing in the context of teaching climate change. International Journal of Science and Mathematics Education, 13(1), 165-190. Blair, A. (2016) Making and remaking the political: lessons from the US experience of civic and political engagement in the teaching of political science, Politics Bridge, D. and Radford, S. (2014). Teaching diplomacy by other means: Using an outside-of-class simulation to teach international relations theory. International Studies Perspectives, 15(4), 423-437. Bursens P., & Jones, R. (2015). The effects of active learning environments: how simulations trigger affective learning. European Political Science. 14(3). 254-265. Chin, J., Dukes, R., & Gamson, W. (2009). Assessment in simulation and gaming A review of the last 40 years. Simulation & Gaming, 40(4), 553-568. DiCicco, J.M. (2014). National security council: Simulating decision-making dilemmas in real time, International Studies Perspectives, 15(4), 438-458. Druckman, D., & Ebner, N. (2013). Games, claims, and new frames: Rethinking the use of simulation in negotiation education. Negotiation Journal, 29(1), 61-92. Duchatelet, D., Bursens, P., Donche, V., Gijbels D., Spooren, P., (2017). Student diversity in a cross-continental EU-simulation. Exploring variation in affective learning outcomes among political science students, forthcoming. Elias, A. (2014). Simulating the European Union: Reflections on module design. International Studies Perspectives, 15(4), 407-422. Freeland, R. M. (2009). Liberal education and effective practice: The necessary revolution in undergraduate education. Liberal Education, 95(1), 6-13. Gijbels, D., Donche, V., Richardson, J.T.E., & Vermunt, J.D. (Eds.)(2014). Learning patterns in higher education: dimensions and research perspectives. New York: Routledge. Gormley-Heenan, C. & Lightfoot, S. (eds.) (2012) Teaching Politics and International Relations. Basingstoke, UK: Palgrave Macmillan. Hidi, S. (2006). Interest. A Unique Motivational Variable. Educational Research review,1(2), 69-82 Hofstede, G. J., De Caluwé, L., & Peters, V. (2010). Why simulation games work-in search of the active substance: A synthesis. Simulation & gaming, 41(6), 824-843. Ishiyama, J. (2013). Frequently Used Active Learning Techniques and their Impact: A Critical Review of Existing Journal Literature in the United States, European Political Science, 12, 116-1206. Ishiyama, J., Miller, W.J., Simon, E. (2016) Handbook on Teaching and Learning in Political Science and International Relations. Cheltenham: Edward Elgar. Jones, R. and Bursens, P. (2015). The effects of active learning environments: How simulations trigger affective learning. European Political Science, 14(3), 254-265. Krain, M. (2010). The effects of different types of case learning on student engagement. International Studies Perspectives, 11(3), 291-308. Krain, M., Kille, K. J., & Lantis, J. S. (2015). Active Teaching and Learning in Cross‐National Perspective. International Studies Perspectives, 16(2), 142-155. Lantis, J. S., Kille, K. J., & Krain, M. (2010). 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Richardson, M., Abraham, C., & Bond, R. (2012). Psychological correlates of university students’ academic performance: A systematic review and meta-analysis. Psychological Bulletin, 138(2), 353-387. Robbins, S. B., Lauver, K., Le, H., David, S., Langley, R., & Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes? A meta-analysis. Psychological Bulletin, 130(2), 261-288. Schellman, S.M., & Turad, K. (2006). Do simulations enhance student learning? An empirical evaluation of an IR simulation. Journal of Political Science Education, 2(1), 19-32. Schnurr, M. A., De Santo, E. M., & Green, A. D. (2014). What do students learn from a role-play simulation of an international negotiation? Journal of Geography in Higher Education, 38(3), 401-414. Simon, E. & Pleschová, G. (eds.) (2012) Teacher Development in Higher Education: Existing Programs, Program Impact, and Future Trends. New York: Routledge. Usherwood, S. (2013). 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