Empowering Learning: Standalone, Browser-Only Courses for Seamless Education

Massive Open Online Courses (MOOCs) have transformed the educational landscape, offering scalable and flexible learning opportunities, particularly in data-centric fields like data science and artificial intelligence. Incorporating AI and data science into MOOCs is a potential means of enhancing the learning experience through adaptive learning approaches. In this context, we introduce PyGlide, a proof-of-concept open-source MOOC delivery system that underscores autonomy, transparency, and collaboration in maintaining course content. We provide a user-friendly, step-by-step guide for PyGlide, emphasizing its distinct advantage of not requiring any local software installation for students. Highlighting its potential to enhance accessibility, inclusivity, and the manageability of course materials, we showcase PyGlide's practical application in a continuous integration pipeline on GitHub. We believe that PyGlide charts a promising course for the future of open-source MOOCs, effectively addressing crucial challenges in online education

Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference

In modern computer science education, massive open online courses (MOOCs) log thousands of hours of data about how students solve coding challenges. Being so rich in data, these platforms have garnered the interest of the machine learning community, with many new algorithms attempting to autonomously provide feedback to help future students learn. But what about those first hundred thousand students? In most educational contexts (i.e. classrooms), assignments do not have enough historical data for supervised learning. In this paper, we introduce a human-in-the-loop "rubric sampling" approach to tackle the "zero shot" feedback challenge. We are able to provide autonomous feedback for the first students working on an introductory programming assignment with accuracy that substantially outperforms data-hungry algorithms and approaches human level fidelity. Rubric sampling requires minimal teacher effort, can associate feedback with specific parts of a student's solution and can articulate a student's misconceptions in the language of the instructor. Deep learning inference enables rubric sampling to further improve as more assignment specific student data is acquired. We demonstrate our results on a novel dataset from Code.org, the world's largest programming education platform.Comment: To appear at AAAI 2019; 9 page

MOOCs as open online learning tools for developing competences related to digital health and social care services for multidisciplinary students

Digital health and social care services are increasing worldwide, and the rapidly changing nature of the world is creating a need for new competences among health and social care students and professionals. The purpose of this paper is to describe the pedagogical solutions of the SotePeda 24/7 national educational development project and to explore especially the massive open online courses (MOOCs) related to digital health and social care services as open (CC BY-SA 4.0) and flexible opportunities for developing the competence of multidisciplinary students and professionals. The data were collected via an online questionnaire from 266 Finnish University of Applied Science (UAS) students participating in the 20 MOOCs piloted during the spring 2020 semester. The majority of the participants (87.6%) came from the health and social care fields. From the 913 registrees, 562 (62%) completed the MOOCs. While piloting the MOOCS, the COVID-19 pandemic influenced heavily, and this may have increased the number of participants in the MOOCs, but also affecting the MOOCs in decreased retention and increased number of dropouts. To motivate students to actively complete the MOOCs, most were offered as 1-ECTS credit courses. Shorter study units were used as they were considered more flexible than longer ones, allowing students to find time to complete them more easily. The data were analysed using nonparametric quantitative methods. According to the results, the MOOCs were very successful in offering students flexible and open online learning opportunities and tools for developing their competences. MOOCs can potentially be efficient tools also in developing professionals’ competences and pursuing lifelong learning. There is a fruitful ground in Finland to utilize open online learning opportunities as tools for developing competences because the already wide usage of digital tools and solutions in the country

The study of Coursera’s data science specialization

Мета дослідження: з’ясування суті поняття «specialization» в практиці масових онлайн курсів. Об’єкт дослідження: процес навчання на масових відкритих дистанційних курсах. Предмет дослідження: особливості «data science» спеціалізації проекту Coursera. Завдання дослідження: взяти участь в якості студента в декількох онлайн масових курсах з категорії «data science specialization», з’ясувати сутність і структуру цієї спеціалізації, визначити її особливості, шляхи включення в традиційний навчальний процес українських вузів. Методи дослідження: включене спостереження, контент-аналіз, аналіз продуктів діяльності. Результати дослідження: спеціалізація Data science проекту Cousera – серія з 9-ти курсів, що охоплюють концепції і засоби аналізу даних, починаючи з постановки дослідницьких питань і закінчуючи публікацією результатів. Послідовність курсів завершується виконанням спеціального проекту (Capstone Project). Курси в серії пов’язані жорсткою і м’якою залежністю. Щомісяця курси повторюються. Структуру курсу становить Сілабус, короткі відеолекції, тести, рeer оцінювання, курсові проекти, форум. Для завдань з програмування використовуються R, RStudio, Git, GitHub. Висновки і рекомендації: шляхи включення такої форми навчання як спеціалізація data science в традиційний навчальний процес українських вузів: оновлення навчально-методичного забезпечення дисциплін, що викладаються, організація самостійної роботи студентів з матеріалами курсів, включення в тематику кваліфікаційних робіт, використання нових засобів і методів, що вивчаються в спеціалізації, в дослідженнях аспірантів і докторантів для аналізу отриманих даних.Objective: To identify the characteristics of the specialization form of the massive open online courses. Research object: a learning process of the massive open online courses. Research subject: Data science specialization of Coursera. Research objectives: to participate as a student in the several online courses in “data science specialization”, to find the structure of this specialization, to determine its characteristics. Methods: participant observation, content analysis. Results: Data science specialization of Cousera project is a series of 9 courses covering concepts and tools of data analysis, from the research questions formulation to results publication. The implementation of a special Capstone Project has completed this sequence of courses. Сourses are repeated once a month during a year. The courses in the specialization are related with a hard and a soft dependences. Course structure consists of syllabus, short video lectures, tests, peer assessment, course projects, forum. The software R, RStudio, Git, GitHub are used for programming assignment. Conclusions and recommendations: there are next ways to aggregate this form in the traditional educational process of Ukrainian universities: developing training and methodological support of disciplines, the students work organization with course materials, including the topics in qualification works, using new data analysis tools and techniques in the post graduate and post doctoral studies

Establishing a Data Science 101 Pedagogy: Reimagining the MOOC Learning Experience Through a Case-Based Learning Methodology

This paper was created as part of CS6460 Educational Technology at Georgia Tech.This work involved a comparative analysis of randomly selected Data Science Massive Open Online Courses (MOOCs) and master’s degree programs in investigating how effectively interdisciplinary curricula approaches were being utilized in the course design. It also involved a second study, in the form of a qualitative survey, that asked students to share their perspective, satisfaction, and sentiment from MOOC experiences. These findings were combined, analyzed and utilized to support the foundation of the proposed case-based learning methodology. This approach provides a more real-world and project simulated approach that challenges students to solve problems analytically which is seen as a more effective framework for delivering data science offerings

MOOCs, Learning Analytics and Learning Advisors

The advent of Massive Open Online Courses has been variously described as heralding the end of the modern university or alternatively, an over-hyped re-badging of existing online content whose advantages have already been realised. Appeals to ideology however, have typically characterised coverage of both polarities rather than hard evidence; in particular, there has been much less analysis on just how learning outcomes are impacted by either “face-to-face” interaction or online/digital environment. Less dichotomously and even more rarely addressed is perhaps a more pertinent question: What blending of the two learning modes works best and in what circumstances? In this paper we argue that the emerging field of learning analytics applied to “educational big data” contains the tools for answering such a question provided a university’s data linkage problem can be solved. The authors, Learning Advisors in ECU’s Faculty of Engineering, Health and Science, describe the initiation of a framework incorporating data on content usage in online learning systems, together with establishing a new system for collecting data on individual consultations and workshops (a “face-to-face” mode, for which data is less-commonly collected). These data are presented and even in isolation contain interesting features on ECU’s current learning landscape; it is in their combination, however, that we argue the real potential lies and we conclude by covering the necessary steps needed for such a realisation

Twitter as a Tool for Teaching and Communicating Microbiology: The #microMOOCSEM Initiative

Online social networks are increasingly used by the population on a daily basis. They are considered a powerful tool for science communication and their potential as educational tools is emerging. However, their usefulness in academic practice is still a matter of debate. Here, we present the results of our pioneering experience teaching a full Basic Microbiology course via Twitter (#microMOOCSEM), consisting of 28 lessons of 40-45 minutes duration each, at a tweet per minute rate during 10 weeks. Lessons were prepared by 30 different lecturers, covering most basic areas in Microbiology and some monographic topics of general interest (malaria, HIV, tuberculosis, etc.). Data analysis on the impact and acceptance of the course were largely affirmative, promoting a 330% enhancement in the followers and a >350-fold increase of the number of visits per month to the Twitter account of the host institution, the Spanish Society for Microbiology. Almost one third of the course followers were located overseas. Our study indicates that Massive Online Open Courses (MOOC) via Twitter are highly dynamic, interactive, and accessible to great audiences, providing a valuable tool for social learning and communicating science. This strategy attracts the interest of students towards particular topics in the field, efficiently complementing customary academic activities, especially in multidisciplinary areas like Microbiology.Versión del edito

MOOCs as part of the university curriculum: A case study

Massive Open Online Courses (MOOCs) sind seit 2012 ein fester Bestandteil der Bildungslandschaft. In den letzten zehn Jahren haben sie einerseits eine massive Entwicklung erfahren, die mit dem Aufkommen von Plattformen wie Coursera, edX, Udemy oder FutureLearn verbunden ist. Gleichzeitig ist jedoch klar geworden, dass sie nicht als Ersatz für die traditionelle formale Universitätsausbildung angesehen werden können. Am Fachbereich für Informationsstudien und Bibliothekswesen der Masaryk-Universität werden MOOCs den Studierenden als Teil eines bestimmten Kurses angeboten, in dem sie Unterstützung und Feedback erhalten. Das Lernen ist auch mit Credits verbunden, was die Motivation der Studierenden, den Kurs zu absolvieren, erhöht. Die Forschung wird mit Daten aus Fragebögen in der ersten Woche und am Ende des Kurses arbeiten (n=18). Auf der Grundlage der Daten werden wir Erkenntnisse für die Durchführung anderer ähnlicher Kurse anbieten. Die Unterstützung durch die Universität in Form von Motivation und einem Gefühl der Sicherheit ist entscheidend. Die Studierenden weisen hohe Abschlussquoten auf, wenn sie den Kurs als Teil ihres Lehrplans belegen. Andererseits nennen sie ihre Unfähigkeit, gut mit der Zeit umzugehen und ihre Aufgaben zu organisieren, als ein wesentliches Hindernis.Massive Open Online Courses (MOOCs) have been widely part of the educational landscape since 2012. Over the last decade, they have seen, on the one hand, a massive development associated with the emergence of platforms such as Coursera, edX, Udemy or FutureLearn. Still, at the same time, it has become clear that they cannot be considered as a substitute for traditional formal university education. At the Department of Information Studies and Library Science at Masaryk University, MOOCs are offered to students as part of a particular course in which they receive support and feedback. The learning is also linked to credits, which increases students' motivation to complete the course. The research will work with data from questionnaires in the first week and at the end of the course (n=18). The research will offer insights for running other similar courses based on the data. University support in terms of motivation and a sense of security is crucial. Students show high completion rates if they study the course as part of their curriculum. On the other hand, they name their inability to work well with time and organise their tasks as a significant barrier