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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.
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.
Veränderte Anforderungen an eine europäische Standardisierungspolitik in der Telekommunikation
(1996)
The case for a more binding WTO agreement on regulatory principles in telecommunication markets
(1999)
Veränderte Anforderungen an eine europäische Standardisierungspolitik in der Telekommunikation
(1997)
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.
Next Generation Access Networks: Why is there a higher risk of investment and how to deal with it?
(2009)
AI-based systems are nearing ubiquity not only in everyday low-stakes activities but also in medical procedures. To protect patients and physicians alike, explainability requirements have been proposed for the operation of AI-based decision support systems (AI-DSS), which adds hurdles to the productive use of AI in clinical contexts. This raises two questions: Who decides these requirements? And how should access to AI-DSS be provided to communities that reject these standards (particularly when such communities are expert-scarce)? This chapter investigates a dilemma that emerges from the implementation of global AI governance. While rejecting global AI governance limits the ability to help communities in need, global AI governance risks undermining and subjecting health-insecure communities to the force of the neo-colonial world order. For this, this chapter first surveys the current landscape of AI governance and introduces the approach of relational egalitarianism as key to (global health) justice. To discuss the two horns of the referred dilemma, the core power imbalances faced by health-insecure collectives (HICs) are examined. The chapter argues that only strong demands of a dual strategy towards health-secure collectives can both remedy the immediate needs of HICs and enable them to become healthcare independent.
Extracting workflow nets from textual descriptions can be used to simplify guidelines or formalize textual descriptions of formal processes like business processes and algorithms. The task of manually extracting processes, however, requires domain expertise and effort. While automatic process model extraction is desirable, annotating texts with formalized process models is expensive. Therefore, there are only a few machine-learning-based extraction approaches. Rule-based approaches, in turn, require domain specificity to work well and can rarely distinguish relevant and irrelevant information in textual descriptions. In this paper, we present GUIDO, a hybrid approach to the process model extraction task that first, classifies sentences regarding their relevance to the process model, using a BERT-based sentence classifier, and second, extracts a process model from the sentences classified as relevant, using dependency parsing. The presented approach achieves significantly better resul ts than a pure rule-based approach. GUIDO achieves an average behavioral similarity score of 0.93. Still, in comparison to purely machine-learning-based approaches, the annotation costs stay low.