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Kein Urteil zum Datenschutzrecht sorgte im vergangenen Jahr für mehr panische Reaktionen als die Entscheidung des EuGH in der Rechtssache “Wirtschaftsakademie Schleswig-Holstein”(C-210/16). Das Urteil warf in datenschutzrechtlicher Literatur und Öffentlichkeit zahlreiche Fragen auf: Ist jetzt jeder “gemeinsam” Verantwortlicher? Was sind die Kriterien? Der EuGH hat kürzlich in einem – dem allgemeinen Vernehmen nach aufsehenerregenden, de facto aber kaum überraschenden – Urteil für Klarheit gesorgt. Dabei hat das Gericht jedoch einige Fragen offengelassen und neue Fragen aufgeworfen. Ein Blick auf alte und neue Herausforderungen in Kooperationsszenarien.
Kurz vor der parlamentarischen Sommerpause hat der Bundestag am 28.6.2019 das 2. Datenschutz-Anpassungs- und Umsetzungsgesetz EU (2. DSAnpUG-EU) beschlossen, der Bundesrat hat diesem Gesetz am 20.9.2019 zugestimmt. Das Artikelgesetz, welches im sog. Omnibusverfahren zahlreiche Gesetze auf Bundesebene ändert, soll zur Vereinheitlichung und Anpassung des Bundesrechts an die seit Mai 2018 geltende Datenschutz-Grundverordnung (DSGVO) beitragen.
EDPB: Europäische Aufsichtsbehörden mit neuen Guidelines zur datenschutzkonformen Einwilligung
(2020)
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.
In Fortschreibung des Jahresrückblicks 2018 (Olbertz, NWB 5/2019 S. 266 ) skizziert der vorliegende Beitrag die jüngsten nennenswerten Entwicklungen im Arbeitsrecht des Jahres 2019. Im Bereich der Gesetzgebung, mit dem sich der erste Teil des Beitrags befasst, betrifft dies etwa das Fachkräfteeinwanderungsgesetz, die angestoßenen Schutzvorschriften für Whistleblower oder das gesetzlich verankerte Recht auf Brückenteilzeit. In der arbeitsrechtlichen höchstrichterlichen Rechtsprechung stand das Jahr 2019 insbesondere im Zeichen des Befristungs- und des Urlaubsrechts. Was hier und darüber hinaus wegweisend war, zeigt der zweite Teil des Beitrags.
Researching the field of business intelligence and analytics (BI & A) has a long tradition within information systems research. Thereby, in each decade the rapid development of technologies opened new room for investigation. Since the early 1950s, the collection and analysis of structured data were the focus of interest, followed by unstructured data since the early 1990s. The third wave of BI & A comprises unstructured and sensor data of mobile devices. The article at hand aims at drawing a comprehensive overview of the status quo in relevant BI & A research of the current decade, focusing on the third wave of BI & A. By this means, the paper’s contribution is fourfold. First, a systematically developed taxonomy for BI & A 3.0 research, containing seven dimensions and 40 characteristics, is presented. Second, the results of a structured literature review containing 75 full research papers are analyzed by applying the developed taxonomy. The analysis provides an overview on the status quo of BI & A 3.0. Third, the results foster discussions on the predicted and observed developments in BI & A research of the past decade. Fourth, research gaps of the third wave of BI & A research are disclosed and concluded in a research agenda.
Verantwortlichkeit, Data Breach, das Ende von Fax & E-Mail: Aufsichtsbehörden mit streitbaren Thesen
(2020)
Domain experts regularly teach novice students how to perform a task. This often requires them to adjust their behavior to the less knowledgeable audience and, hence, to behave in a more didactic manner. Eye movement modeling examples (EMMEs) are a contemporary educational tool for displaying experts’ (natural or didactic) problem-solving behavior as well as their eye movements to learners. While research on expert-novice communication mainly focused on experts’ changes in explicit, verbal communication behavior, it is as yet unclear whether and how exactly experts adjust their nonverbal behavior. This study first investigated whether and how experts change their eye movements and mouse clicks (that are displayed in EMMEs) when they perform a task naturally versus teach a task didactically. Programming experts and novices initially debugged short computer codes in a natural manner. We first characterized experts’ natural problem-solving behavior by contrasting it with that of novices. Then, we explored the changes in experts’ behavior when being subsequently instructed to model their task solution didactically. Experts became more similar to novices on measures associated with experts’ automatized processes (i.e., shorter fixation durations, fewer transitions between code and output per click on the run button when behaving didactically). This adaptation might make it easier for novices to follow or imitate the expert behavior. In contrast, experts became less similar to novices for measures associated with more strategic behavior (i.e., code reading linearity, clicks on run button) when behaving didactically.
This publication is intended to present the current state of research on the rebound effect. First, a systematic literature review is carried out to outline (current) scientific models and theories. Research Question 1 follows with a mathematical introduction of the rebound effect, which shows the interdependence of consumer behaviour, technological progress, and interwoven effects for both. Thereupon, the research field is analysed for gaps and limitations by a systematic literature review. To ensure quantitative and qualitative results, a review protocol is used that integrates two different stages and covers all relevant publications released between 2000 and 2019. Accordingly, 392 publications were identified that deal with the rebound effect. These papers were reviewed to obtain relevant information on the two research questions. The literature review shows that research on the rebound effect is not yet comprehensive and focuses mainly on the effect itself rather than solutions to avoid it. Research Question 2 finds that the main gap, and thus the limitations, is that not much research has been published on the actual avoidance of the rebound effect yet. This is a major limitation for practical application by decision-makers and politicians. Therefore, a theoretical analysis was carried out to identify potential theories and ideas to avoid the rebound effect. The most obvious idea to solve this problem is the theory of a Steady-State Economy (SSE), which has been described and reviewed.