What Stays in Mind? - Retention Rates in Programming MOOCs

This work presents insights about the long-term effects and retention rates of knowledge acquired within MOOCs. In 2015 and 2017, we conducted two introductory MOOCs on object-oriented programming in Java with each over 10,000 registered participants. In this paper, we analyze course scores, quiz results and self-stated skill levels of our participants. The aim of our analysis is to uncover factors influencing the retention of acquired knowledge, such as time passed or knowledge application, in order to improve long-term success. While we know that some participants learned the programming basics within our course, we lack information on whether this knowledge was applied and fortified after the course's end. To fill this knowledge gap, we conducted a survey in 2018 among all participants of our 2015 and 2017 programming MOOCs. The first part of the survey elicits responses on whether and how MOOC knowledge was applied and gives participants opportunity to voice individual feedback. The second part of the survey contains several questions of increasing difficulty and complexity regarding course content in order to learn about the consolidation of the acquired knowledge. We distinguish three programming knowledge areas in the survey: First, understanding of concepts, such as loops and boolean algebra. Second, syntax knowledge, such as specific keywords. Third, practical skills including debugging and coding. We further analyzed the long-term effects separately per participant skill group. While answer rates were low, the collected data shows a decrease of knowledge over time, relatively unaffected by skill level. Application of the acquired knowledge improves the memory retention rates of MOOC participants across all skill levels

Editorial: Massive Open Online Courses und ihre Rolle in der digitalen (Hochschul-)Lehre

Massive Open Online Courses, kurz MOOCs, sind Online-Kurse mit einer großen Zahl an Teilnehmer:innen, die zumeist auf speziellen Plattformen kostenlos zur Verfügung gestellt werden. Mit dem Kurs zur Künstlichen Intelligenz von Sebastian Thrun mit über 160.000 Lernenden fanden MOOCs zunehmend Verbreitung. Spätestens seit der COVID19-Pandemie sind sie nicht mehr aus unserem universitären Hochschulalltag wegzudenken und heute zum Teil integraler Bestandteil von Lehrveranstaltungen. Durch vielfältige Einsatzmöglichkeiten werden so Weiterbildungen, Workshops oder joint lectures unterstützt. Das aktuelle Themenheft rief zu Beiträgen rund um MOOCs auf und erlaubt dadurch einen Einblick in die facettenreichen Entwicklungen. In der aktuellen Ausgabe finden Sie hierzu spannende Beiträge mit Erfahrungsberichten, neuesten Erkenntnissen, Weiterentwicklungen und didaktischen Einsatzmöglichkeiten. Wir laden Sie also herzlich ein, mit uns gemeinsam dieses innovative, zukunftsträchtige und auch nachhaltige Thema weiter zu vertiefen

Scale Up Multilingualism in Health Emergency Learning : Developing an Automated Transcription and Translation Tool

World Health Organization's (WHO) emergency learning platform OpenWHO provided by Hasso Plattner Institut (HPI) delivered online learning in real-time and in multiple languages during the COVID-19 pandemic. The challenge was to move from manual transcription and translation to automated to increase the speed and quantity of materials and languages available. TransPipe tool was introduced to facilitate this task. We describe the TransPipe development, analyze its functioning and report key results achieved. TransPipe successfully connects existing services and provides a suitable workflow to create and maintain video subtitles in different languages. By the end of 2022, the tool transcribed nearly 4,700 minutes of video content and translated 1,050,700 characters of video subtitles. Automated transcription and translation have enormous potential as a public health learning tool, allowing the near-simultaneous availability of video subtitles on OpenWHO in many languages, thus improving the usability of the learning materials in multiple languages for wider audiences.publishedVersionPeer reviewe

Metastandard für den internationalen Austausch von MOOCs – der MOOChub als erster Prototyp

Der MOOChub ist eine Webseite, die weit über 700 Massive Open Online Courses (MOOCs) aus dem deutschsprachigen Raum von insgesamt neun unterschiedlichen Partner:innen listet. Damit eine solche Seite automatisiert aufgebaut werden kann, ist es notwendig, dass alle Partner:innen die Metadaten der Kurse in gleicher Weise beschreiben und verfügbar machen. Dieser Artikel beschreibt zunächst die Entstehung der Idee eines gemeinsamen Standards und wie dieser im Anschluss entwickelt worden ist. Das Ergebnis ist einerseits ein offen lizenzierter Quasi-Standard, der sich an üblichen Standards orientiert, und ein erster Prototyp, der sogenannte MOOChub, auf dem nun alle Kurse auffindbar und durchsuchbar sind. Abschließend wird über die nächsten möglichen und auch notwendigen Entwicklungen berichtet, die die Schnittstelle weiter optimieren sollen

Harnessing technology to respond to the global demand for learning during the COVID-19 pandemic

The COVID-19 pandemic generated an unprecedented global demand for learning about the disease and how to manage it. This paper draws on theWorld Health Organization (WHO)'s experience of COVID-19 knowledge-transfer to a worldwide audience of millions of learners registered on OpenWHO, WHO's massive open online course platform. It aims to illustrate the technological solutions that WHO, in collaboration with the Hasso Plattner Institute (HPI), OpenWHO's platform provider, employed in response to the unique challenges this surge in demand for learning engendered. Data on OpenWHO use, including geographic patterns and certificate attainment, were extracted from OpenWHO's internal and external reporting systems. Descriptive analysis was employed to identify trends and compare OpenWHO use with COVID-19 caseload in each WHO region. Data on the OpenWHO system load were obtained from the OpenWHO load balancer (HAProxy). The OpenWHO team responded to the need for trustworthy, evidence-based knowledge on COVID-19 via three main avenues: increased scale, targeting the needs of affected and underserved communities, and prioritising multilingualism. Each approach brought novel problems, which WHO and HPI leveraged their collaboration to meet by employing technology. This included increasing server bandwidth, expanding support teams, adding new language capabilities, and deploying functions to streamline workflows and boost learner experience. In doing so, the ability to effectively and efficiently harness technology became a critical step towards empowering learning's life-saving potential during the COVID-19 pandemic.publishedVersionPeer reviewe

Continuous Intraoperative Recurrent Laryngeal Nerve Monitoring: Techniques, Applications, and Controversies

<jats:title>Abstract</jats:title><jats:sec> <jats:title>Purpose of Review</jats:title> <jats:p>Purpose of the present review is to illustrate the current state of the art concerning continuous intraoperative recurrent laryngeal nerve monitoring (cIONM) for thyroid surgery.</jats:p> </jats:sec><jats:sec> <jats:title>Recent Findings</jats:title> <jats:p>cIONM potentially leads to an improved postoperative vocal cord palsy rate, compared to the intermittent technique. There are currently two main approaches for cIONM: either conventional cIONM based on vagal nerve stimulation or experimental methods, which do not require the positioning of a vagal nerve electrode. One of these methods is the recently described technique “LAR-cIONM,” which utilizes the laryngeal adductor reflex.</jats:p> </jats:sec><jats:sec> <jats:title>Summary</jats:title> <jats:p>cIONM represents an advancement of intermittent nerve monitoring, which allows for an immediate reaction to signal changes. Threshold values and guidelines to prevent recurrent laryngeal nerve palsy were validated for the direct stimulation of the vagal nerve and require verification for alterative cIONM methods, including LAR-cIONM.</jats:p> </jats:sec&gt

Cellular Automata as an Example for Advanced Beginners’ Level Coding Exercises in a MOOC on Test Driven Development

Programming tasks are an important part of teaching computer programming as they foster students to develop essential programming skills and techniques through practice.  The design of educational problems plays a crucial role in the extent to which the experiential knowledge is imparted to the learner both in terms of quality and quantity. Badly designed tasks have been known to put-off students from practicing programming. Hence, there is a need for carefully designed problems. Cellular Automata programming lends itself as a very suitable candidate among problems designed for programming practice. In this paper, we describe how various types of problems can be designed using concepts from Cellular Automata and discuss the features which make them good practice problems with regard to instructional pedagogy. We also present a case study on a Cellular Automata programming exercise used in a MOOC on Test Driven Development using JUnit, and discuss the automated evaluation of code submissions and the feedback about the reception of this exercise by participants in this course. Finally, we suggest two ideas to facilitate an easier approach of creating such programming exercises

Cellular Automata as an Example for Advanced Beginners’ Level Coding Exercises in a MOOC on Test Driven Development

Programming tasks are an important part of teaching computer programming as they foster students to develop essential programming skills and techniques through practice.  The design of educational problems plays a crucial role in the extent to which the experiential knowledge is imparted to the learner both in terms of quality and quantity. Badly designed tasks have been known to put-off students from practicing programming. Hence, there is a need for carefully designed problems. Cellular Automata programming lends itself as a very suitable candidate among problems designed for programming practice. In this paper, we describe how various types of problems can be designed using concepts from Cellular Automata and discuss the features which make them good practice problems with regard to instructional pedagogy. We also present a case study on a Cellular Automata programming exercise used in a MOOC on Test Driven Development using JUnit, and discuss the automated evaluation of code submissions and the feedback about the reception of this exercise by participants in this course. Finally, we suggest two ideas to facilitate an easier approach of creating such programming exercises