The learning effects of United Nations simulations in political science classrooms
Bibliographic Data
| ID | 12870335 |
|---|---|
| Authors | Julia Leib (0000-0003-2960-2403, University of Potsdam, corresponding author), Samantha Ruppel (0000-0001-8232-0996, Goethe University Frankfurt) |
| Year | 2020 |
| Volume | 19 |
| Issue | 3 |
| Pages | 336-351 |
| Publication date | 2020-05-31 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | European Political Science (JOURNAL) |
| Journal identifiers | ISSN: 1680-4333 • E-ISSN: 1682-0983 |
| Publisher | Palgrave Macmillan (PUBLISHER • GB) |
| DOI | 10.1057/s41304-020-00260-3 |
| OpenAlex | W3034160176 |
| Language | EN |
| Citations received | 5 |
| References cited | 14 |
How do active learning environments—by means of simulations—enhance political science students’ learning outcomes regarding different levels of knowledge? This paper examines different UN simulations in political science courses to demonstrate their pedagogical value and provide empirical evidence for their effectiveness regarding three levels of knowledge (factual, procedural and soft skills). Despite comprehensive theoretical claims about the positive effects of active learning environments on learning outcomes, substantial empirical evidence is limited. Here, we focus on simulations to systematically test previous claims and demonstrate their pedagogical value. Model United Nations (MUNs) have been a popular teaching device in political science. To gain comprehensive data about the active learning effects of MUNs, we collect data and evaluate three simulations covering the whole range of simulation characteristics: a short in-class simulation of the UN Security Council, a regional MUN with different committees being simulated, and two delegations to the National Model United Nations, for which the students prepare for 1 year. Comparative results prove that simulations need to address certain characteristics in order to produce extensive learning outcomes. Only comprehensive simulations are able to achieve all envisioned learning outcomes regarding factual and procedural knowledge about the UN and soft skills
Active learning (machine learning · Comparative politics · Empirical evidence · Epistemology · Mathematics education · Political science · Politics · Test (biology · Value (mathematics · Computer Science · Innovative Teaching Methodologies in Social Sciences · Law · Psychology · Artificial Intelligence
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| Unique citing works | 5 |
|---|---|
| Citations per year | 1 |
| Citation span | 2021 - 2025 (5) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 5 |