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Im Jahr 2015 wurden in Deutschland über drei Millionen Benzinautos und lediglich 12.363 Elektroautos neu zugelassen. Das ursprünglich von der Bundesregierung vorgegebene Ziel, dass bis 2020 eine Million E-Autos auf deutschen Straßen fahren (und bis 2030 sechs Millionen), rückt damit in immer weitere Ferne. Um das Ziel dennoch zu erreichen, plant die Bundesregierung nun eine staatliche Prämie für den Kauf von Elektroautos: Umwelt-, Verkehrs- und Wirtschaftsministerium haben gemeinsam ein Konzept entworfen, dem zufolge private Käufer zukünftig einen Zuschuss von 5.000 Euro beim Erwerb eines Elektroautos bekommen sollen. 40 Prozent dieses Zuschusses soll von den Autoherstellern getragen werden. Das Programm, das weitere ausgabenwirksame öffentliche Maßnahmen vorsieht, würde Kosten in Milliardenhöhe verursachen. Die beabsichtigte Subventionierung wirft die Frage auf, ob diese wirtschaftlich sinnvoll sind.
Eye movement modelling examples (EMME) are instructional videos that display a
teacher’s eye movements as “gaze cursor” (e.g. a moving dot) superimposed on the
learning task. This study investigated if previous findings on the beneficial effects of EMME would extend to online lecture videos and compared the effects of displaying the teacher’s gaze cursor with displaying the more traditional mouse cursor as a tool to guide learners’ attention. Novices (N = 124) studied a pre-recorded video lecture on how to model business processes in a 2 (mouse cursor absent/present) × 2 (gaze cursor absent/present) between-subjects design. Unexpectedly, we did not find significant effects of the presence of gaze or mouse cursors on mental effort and learning. However, participants who watched videos with the gaze cursor found it easier to follow the teacher. Overall, participants responded positively to the gaze cursor, especially when the mouse cursor was not displayed in the video.
In this article, we introduce how eye-tracking technology might become a promising tool to teach programming skills, such as debugging with ‘Eye Movement Modeling Examples’ (EMME). EMME are tutorial videos that visualize an expert's (e.g., a programming teacher's) eye movements during task performance to guide students’ attention, e.g., as a moving dot or circle. We first introduce the general idea behind the EMME method and present studies that showed first promising results regarding the benefits of EMME to support programming education. However, we argue that the instructional design of EMME varies notably across them, as evidence-based guidelines on how to create effective EMME are often lacking. As an example, we present our ongoing research on the effects of different ways to instruct the EMME model prior to video creation. Finally, we highlight open questions for future investigations that could help improving the design of EMME for (programming) education.