Using Mobile Devices in Teaching Large University Classes: How Does It Affect Exam Success?

Exploring (Collaborative) Generation and Exploitation of Multiple Choice Questions: Likes as Quality Proxy Metric

Multiple Choice Questions (MCQs) are an established medium of formal educational contexts. The collaborative generation of MCQs by students follows the perspectives of constructionist and situated learning and is an activity that fosters learning processes. The MCQs generated are—besides the learning processes—further outcomes of collaborative generation processes. Quality MCQs are a valuable resource, so that collaboratively generated quality MCQs might also be exploited in further educational scenarios. However, the quality MCQs first need to be identified from the corpus of all generated MCQs. This article investigates whether Likes distributed by students when answering MCQs are viable as a metric for identifying quality MCQs. Additionally, this study explores whether the process of collaboratively generating MCQs and using the quality MCQs generated in commercial quiz apps is achievable without additional extrinsic motivators. Accordingly, this article describes the results of a two-stage field study. The first stage investigates whether quality MCQs may be identified through collaborative inputs. For this purpose, the Reading Game (RG), a gamified, web-based software aiming at collaborative MCQ generation, is employed as a semester-accompanying learning activity in a bachelor course in Urban Water Management. The reliability of a proxy metric for quality calculated from the ratio of Likes received and appearances in quizzes is compared to the quality estimations of domain experts for selected MCQs. The selection comprised the ten best and the ten worst rated MCQs. Each of the MCQs is rated regarding five dimensions. The results support the assumption that the RG-given quality metric allows identification of well-designed MCQs. In the second stage, MCQs created by RG are provided in a commercial quiz app (QuizUp) in a voluntary educational scenario. Despite the prevailing pressure to learn, neither the motivational effects of RG nor of the app are found in this study to be sufficient for encouraging students to voluntarily use them on a regular basis. Besides confirming that quality MCQs may be generated by collaborative software, it is to be stated that in the collaborative generation of MCQs, Likes may serve as a proxy metric for the quality of the MCQs generated.

Learning With a Double-Edged Sword? Beneficial and Detrimental Effects of Learning Tests-Taking a First Look at Linkages Among Tests, Later Learning Outcomes, Stress Perceptions, and Intelligence

It has often been shown that tests as intentionally hindered and difficult learning tasks increase long-term learning compared to easier tasks. Previous work additionally indicated that higher intelligence might serve as a prerequisite for such beneficial effects of tests. Nevertheless, despite their long-term learning effects, tests were also found to be evaluated as more negative and to lead to more stress and anxiety compared to easier control tasks. Stress and anxiety, in turn, often yield detrimental effects on learning outcomes. Hence, we hypothesized that tests increase later learning outcomes but simultaneously also lead to more stress perceptions. Such increased stress was, in turn, hypothesized to reduce later learning outcomes (thus, stress might serve as a mediator of the beneficial effects of tests on learning). All these assumed effects should further be moderated by intelligence, insofar as that higher intelligence should increase beneficial effects of tests on learning, should decrease stress perceptions caused by tests, and should reduce detrimental effects of stress on learning outcomes. Higher intelligence was also assumed to be generally associated with higher learning. We conducted a laboratory study (N=89) to test these hypotheses: Participants underwent an intelligence screening, then worked on either a test or a re-reading control task, and reported their immediate stress perceptions. Later learning outcomes were assessed after 1week. The results supported all assumed main effects but none of the assumed interactions. Thus, participants using tests had higher long-term learning outcomes compared to participants using re-reading tasks. However, participants using tests also perceived more immediate stress compared to participants that only re-read the materials. These stress perceptions in turn diminished the beneficial effects of tests. Stress was also generally related to lower learning, whereas higher intelligence was linked to higher learning and also to lower stress. Hence, our findings again support the often assumed benefits of tests-even when simultaneously considering learners' intelligence and and when considering the by tests caused stress perceptions. Notably, controlling for stress further increases these long-term learning benefits. We then discuss some limitations and boundaries of our work as well as ideas for future studies.