Will education become more open?

Open science practitioners embrace the ideas of sharing and communicating their research and interests as well as collaborating with like-minded peers, i.e., practicing co-science (McKiernan et al. 2016) such as on the Open Science MOOC platform. If they admit to those goals regarding their research, it can be assumed that those researchers adapt their attitudes and practices towards learning and teaching, respectively. So, if researchers move towards open science practices, will they do so in their higher education teaching? Will education become more open? More generally, what would open science principles (Bezjak et al. 2018) in education look like, for educators and learners, respectively? (DIPF/Orig.

Street Needs: Are Hawai‘i Homeless Teens Information Poor?

M.A. Thesis. University of Hawaiʻi at Mānoa 2017

How many sources are neded? The effects of bibliographic databases on systematic review outcomes. [Preprint]

Systematic reviews are an established method to synthesize the current state of research for a specific question to make evidence-based decisions in research, politics, and practice. A key activity of a review approach is a systematic and comprehensive search strategy to find all potentially relevant literature. Although guidelines and handbooks address relevant methodological aspects and recommend strategies, the right choice of databases and information sources is unclear. Specifically in educational research, an interdisciplinary field, with no core database at hand and multiple potentially relevant sources available, investigators lack guidance for choosing the most appropriate ones. The presented study investigates the coverage in terms of scope, similarity and combination efficiency of seven multidisciplinary, discipline-specific and nationally focused databases. The evaluation is based on relevant assessed literature of two extensive recently published reviews in German educational research that serve as gold standard to evaluate the databases. Results indicate distinct variations in the databases, while also detecting databases with equal coverage. The paper contributes to guidance in choosing databases for educational review studies, while stressing that this process depends on a review\u27s topical and geographical focus. Moreover, general implications resulting from the study refer to the relevance of database choice for review outcomes, the careful consideration of diverse search strategies beyond database search and a rigorous documentation of database inclusion and exclusion criteria. (DIPF/Orig.

Information literacy and its interplay with AI

Information literacy (IL) – and similarly digital literacy – want to convey skills to handle information and data, its use and the creation of new information and services. It emphasizes to teach competencies that enable learners to adapt to new environments and thus foster life-long learning. Artificial intelligence systems (AI) enter all kinds of areas, specifically the educational sector on all levels. For example, learning analytics and learning supportive services are established. Learners might see the opportunities of those services that promise to foster individual learning and skill development. At the same time, they need to develop novel kinds of literacy to understand and to apply AI. Thus, IL teaching and literacy frameworks need to consider an adaptation to recent changes that come with AI. Our contribution wants to start a discussion within the IL expert field on how IL teaching needs to prepare learners for the new era of AI. We will discuss if IL teaching frameworks need to be adapted to foster AI literacy and moreover, how IL teaching concept can benefit from developments in AI. Based on ascoping review in AI in education, we will introduce current ideas of AI technology and applications and discuss them in relation to IL teaching schemes. Following up the dialog of our IL working group, we want to contribute to current discussions on AI in education and the potential influence it might have on IL teaching, and reversely. (DIPF/Orig.

Who Takes Responsibility for AI? A Field Study on AI-Related Task Shifts, Explainability, and Responsibility Attributions

The opaque and incomprehensible nature of artificial intelligence (AI) raises questions about who can and will take responsibility for AI in organizations. Examining the relation between explainability and responsibility, we explore how AI responsibility attributions unfold when 1) AI shifts tasks and roles of individuals and 2) these individuals lack comprehension of the task elements they are expected to take responsibility for. Through an in-depth qualitative field study in a large organization, we identify three types of responsibility attributions in decision-making with AI: a shared responsibility, a data science-centered responsibility, and a business domain expert-centered responsibility. These three prevalent types of responsibility attributions will be explained by the interaction of different shifts in AI-related tasks and corresponding AI explainability needs and actions in the organization. Our study contributes to the existing literature by demonstrating AI\u27s impact on traditional responsibility assignment in day-to-day organizational practices

Reflecting open practices on digital infrastructures. Functionalities and implications of knowledge. [Preprint]

Open practices in education focus on the actions of learners and teachers regarding openness. The sharing and collaborative creation of open educational resources is at the core of such practices. Digital infrastructures do not only provide environments for these kinds of practices but reflect ide-as and implications of open practices through the functionalities they offer. Those infrastructures can be seen as drivers for enabling open practices to become default. However, a common understanding of open practices has yet to be defined. As such, designing digital infrastructures that foster open prac-tices might be a challenge. This chapter shows the relation between open practices and digital infrastructures. (DIPF/Orig.

Open Practices of Early Career Researchers: A Qualitative Study on Research and Teaching Behavior

Many researchers have a positive attitude towards open science and are motivated to apply them. However, applying them requires a change in one’s daily practices. Different factors might challenge a behavioral change. The introduced study wants to get deeper insights into the reasons and influences that lead early career researchers to apply open practices in their daily research and teaching work. The participatory design let ten participants choose open practices they wanted to learn and adapt in either research or teaching scenarios. The study accompanied them and collected their positive and challenging experiences via diverse methods like interviews, diary entries and workshops. This paper introduces the study design and preliminary results

Openness in Higher Education:: Potentials for Open Educational Practices in Research-based Learning Concepts

Dieser Artikel befasst sich mit zwei Lehr-/Lernansätzen, die aktuell stark diskutiert werden. Beiden ist gemeinsam, dass sie die Selbstständigkeit und die hohe Aktivität der Lernenden in den Mittelpunkt stellen (selbstreguliertes Lernen) und einen Fokus auf das kollaborative Arbeiten (soziales Lernen) legen. Forschendes Lernen zeichnet sich dadurch aus, dass es die wissenschaftliche Ausbildung an Hochschulen durch forschende Tätigkeiten der Studierenden umsetzen will. Offene Lehr-/Lernpraktiken (Open Educational Practices) werden in Zusammenhang mit der Öffnung von Lehre diskutiert, beinhalten in der Umsetzung jedoch auch Aspekte, die für eine offene Wissenschaft (Open Science) von Bedeutung sind. Sollen Studierende durch forschendes Lernen in Wissenschaft hineinwachsen, so spielt die Öffnung der Wissenschaft auch für sie eine Rolle. In unserem Beitrag diskutieren wir den Begriff der Offenheit aus diesen unterschiedlichen Perspektiven und gehen der Frage nach, inwieweit sich Aspekte offener Lehr-/Lernpraktiken in das Konzept des forschenden Lernens integrieren lassen. Wir schlagen eine Matrix vor, um die Offenheit im forschenden Lernen anhand der Merkmale offener Lehr-/Lernpraktiken sowie verschiedener Varianten forschenden Lernens zu vergleichen und diskutieren die Relevanz der Ansätze für die offene Wissenschaft. Die Zusammenführung von offenen Lehr-/Lernpraktiken und forschendem Lernen kann erste Einblicke geben, wie sich die an Hochschulen stattfindenden Öffnungsprozesse auf die wissenschaftliche Ausbildung auswirken.This article describes the commonalities of open educational practices (OEP) and research-based learning. Both concepts focus on the learners' high activity (self-regulated learning) as well as collaborative aspects (social learning). Research-based Learning aims to base education on the principles of research and to let students experience what it means to practice research. Open educational practices are discussed within the principles of open education and at the same time refer to practices in open science. Assuming that students are supposed to become part of the science system by Research-based Learning the process of opening science affects them as well. We will discuss the term ‹openness› from different perspectives and investigate how we can integrate aspects of open educational practices into concepts of research-based learning. We propose a matrix to compare and evaluate openness in research-based learning based on characteristics of open educational practices. We as well discuss its relevance for open science. The integration of open educational practices into research-based learning concepts gives first insights on how open education impacts and contributes to the teaching and learning of research literacies for future scientists

Science 2.0 & open science in higher education

[no abstract available

Open practice in science and education – a discussion with researchers and educators who tested to be open

How can we make the shift from closed to open practice in research and education? What are incentives for researchers to apply open science and open educational practices, and what hinders them to do so? The OPER study (Open Practices of Educational Researchers), funded by the Leibniz Research Alliance Open Science, investigates those questions. Study participants chose open scenarios for their daily research or teaching practices and tested them for six to 12 month. They wrote down their experiences with and opinions on open practices in dairies. The starting workshop was held in April 2019 with the first round of participants. First discussions on relevant topics were collected in Wikiversity and online pads.Wie können offene Praktiken im Lehr- und Forschungsalltag umgesetzt werden? Was sind die Anreize, offene Wissenschaft und offene Lehre zu praktizieren, und was hält uns davon ab? Die vom Leibniz-Forschungsverbund Open Science geförderte OPER-Studie (Open Practices of Educational Researchers) wollte dies herausfinden und ließ Bildungsforscher*innen offene Praktiken während eines Zeitraums von 6 bis 12 Monaten in unterschiedlichen Anwendungsfällen testen. Ihre Erfahrungen und Meinungen hielten sie in Tagebucheinträgen fest