Jan Renz

Towards practical programming exercises and automated assessment in Massive Open Online Courses

In recent years, Massive Open Online Courses (MOOCs) have become a phenomenon presenting the prospect of free high class education to everybody. They bear a tremendous potential for teaching programming to a large and diverse audience. The typical MOOC components, such as video lectures, reading material, and easily assessable quizzes, however, are not sufficient for proper programming education. To learn programming, participants need an option to work on practical programming exercises and to solve actual programming tasks. It is crucial that the participants receive proper feedback on their work in a timely manner. Without a tool for automated assessment of programming assignments, the teaching teams would be restricted to offer optional ungraded exercises only. The paper at hand sketches scenarios how practical programming exercises could be provided and examines the landscape of potentially helpful tools in this context. Automated assessment has a long record in the history of computer science education. We give an overview of existing tools in this field and also explore the question what can and/or should be assessed.

Improving the Peer Assessment Experience on MOOC Platforms

Massive Open Online Courses (MOOCs) have revolutionized higher education by offering university-like courses for a large amount of learners via the Internet. The paper at hand takes a closer look on peer assessment as a tool for delivering individualized feedback and engaging assignments to MOOC participants. Benefits, such as scalability for MOOCs and higher order learning, and challenges, such as grading accuracy and rogue reviewers, are described. Common practices and the state-of-the-art to counteract challenges are highlighted. Based on this research, the paper at hand describes a peer assessment workflow and its implementation on the openHPI and openSAP MOOC platforms. This workflow combines the best practices of existing peer assessment tools and introduces some small but crucial improvements.

CodeOcean - A versatile platform for practical programming excercises in online environments

The paper at hand introduces CodeOcean, a web-based platform to provide practical programming exercises. CodeOcean is designed to be used in Massive Open Online Courses (MOOCs) to teach programming to beginners. Its concept and implementation are discussed with regard to tools provided to students and teachers, sandboxed and scalable code execution, scalable assessment, and interoperability. MOOCs bear a tremendous potential for teaching programming to a large and diverse audience. Learning to program, however, is a hands-on effort; watching videos and solving multiple choice tests will not be sufficient. A platform, such as CodeOcean, to work on practical programming exercises and to solve actual programming tasks is required. Due to the massiveness of the courses, teaching teams cannot check, give feedback, or assess the submissions of the participants manually. CodeOcean provides the participants with proper automated feedback in a timely manner and is able to assess the given programming tasks in an automated way.

Lightweight ad hoc assessment of practical programming skills at scale

There is a great demand for hands-on training in engineering education. In the context of a Massive Open Online Course (MOOC), assessing these experiments manually by teaching assistants is not possible owed to the high number of participants and the resulting workload for the teaching team. Systems for machine-based assessment of coding tasks are existing, but not necessarily available publicly, or not prepared to handle the massive amount of users in a MOOC. Definitely, they are not available “ad hoc”, but require a certain amount of effort to be integrated in the MOOC platform or to be made available for the students in another way. Time and money to provide the required effort is not always available. This work presents a lightweight solution for the assessment of practical programming exercises, based on third party online coding tools. The solution was introduced as a part of openHPIs Web-Technologies course. The basic idea is to prepare a task in an available online tool, along with a piece of code that is able to evaluate the participants solution. In case of success the participant is provided with a password, which in return serves as the answer for a fill-in-the-gap question in a standard quiz as provided by the openHPI MOOC platform, and thus allows for automatic online assessment based on practical coding exercises.

Enabling Schema Agnostic Learning Analytics in a Service-Oriented MOOC Platform

This paper at hand describes the design and implementation of an analytics service to retrieve live usage data from students enrolled in a service-oriented MOOC platform for the purpose of learning analytics (LA) research. A real-time and extensible architecture for consolidating and processing data in versatile analytics stores is introduced.

Using A/B testing in MOOC environments

In recent years, Massive Open Online Courses (MOOCs) have become a phenomenon offering the possibility to teach thousands of participants simultaneously. In the same time the platforms used to deliver these courses are still in their fledgling stages. While course content and didactics of those massive courses are the primary key factors for the success of courses, still a smart platform may increase or decrease the learners experience and his learning outcome. The paper at hand proposes the usage of an A/B testing framework that is able to be used within an micro-service architecture to validate hypotheses about how learners use the platform and to enable data-driven decisions about new features and settings. To evaluate this framework three new features (Onboarding Tour, Reminder Mails and a Pinboard Digest) have been identified based on a user survey. They have been implemented and introduced on two large MOOC platforms and their influence on the learners behavior have been measured. Finally this paper proposes a data driven decision workflow for the introduction of new features and settings on e-learning platforms.

Scaling youth development training in IT using an xMOOC platform

The paper at hand evaluates the Massive Open Online Course (MOOC) Spielend Programmieren Lernen (Playfully learning to program), an effort to scale the youth development program at the Hasso Plattner Institute (HPI) for a larger audience. The HPI has a strong tradition in attracting children and adolescents to take their first steps towards a career in IT at an early age. The Schülerakademie, the Schülerkolleg, the Schülerklub, and the support for the CoderDojo in Potsdam are some of the regular activities in this context to take youngsters by the hand and supply them with material and guidance in their mother tongue. With the emergence of MOOCs and the success of HPIs own MOOC Platform - openHPI - it was a natural step to develop a course to address an audience that is only marginally represented in openHPIs regular courses: school children and adolescents. A further novelty for openHPI in this course was the focus on teaching programming with a high percentage of obligatory hands-on tasks. Particularly for this course, a standalone tool allowing participants to write and evaluate code directly in the browser - without the need to install additional software - has been developed. We will compare this tool to a small selection of similar approaches on other platforms. As it will be shown, the course attracted a far more diverse audience than expected, and therefore, also needs to be seen in the context of spreading digital literacy amongst wider parts of society. In this context we also will discuss the significant differences in the usage of the forum between the course Spielend Programmieren Lernen and the course In-Memory Databases, a more traditional openHPI course.

Taking Informed Action on Student Activity in MOOCs

This paper presents a novel approach to understand specific student behavior in MOOCs. Instructors currently perceive participants only as one homogeneous group. In order to improve learning outcomes, they encourage students to get active in the discussion forum and remind them of approaching deadlines. While these actions are most likely helpful, their actual impact is often not measured. Additionally, it is uncertain whether such generic approaches sometimes cause the opposite effect, as some participants are bothered with irrelevant information. On the basis of fine granular events emitted by our learning platform, we derive metrics and enable teachers to employ clustering, in order to divide the vast field of participants into meaningful subgroups to be addressed individually.

Supporting Multi-Device E-Learning Patterns with Second Screen Mobile Applications

Many providers of Massive Open Online Course (MOOC) platforms released mobile applications in the recent years to enable learning offline and on the go, for a more ubiquitous learning experience. However, mainly the MOOC content was optimized for small screens, but mobile devices provide the opportunity to enrich the MOOC experience even further by enabling new forms of learning. Based on a previous learning patterns evaluation and a user survey, this paper presents a second screen prototype for the MOOC platform of the Hasso Plattner Institute, whereby the mobile application can be used as a learning companion while using the web platform on a computer. Four different actions were implemented which can be done next to watching a video lecture. The evaluation showed that the prototype was helpful and made learning more efficient, as reported by users, and also ideas for further improvements were proposed.

Smart MOOC - Social Computing for Learning and Knowledge Sharing

Massive Open Online Courses(MOOCs) make use of educational technologies to deliver learning materials, supposedly open for everyone, usually with a capacity to serve a substantial number of learners regardless of their geographical locations. A recent advancement in mobile technologies and wireless communications in Africa has produced a conducive digital environment enough to support mobile learning. However, only a handful of an audience in Africa participates in online learning correlated to their massive engagement in social networking. Internet-based social media programs make most of the connections with the audience for social purposes and yet far less with educational intentions. Participation in mobile learning is still unnoticeable. Awareness about MOOCs remains very low in comparison to that in social media in the region. Therefore it remains unclear though, in which ways, social media may help to boost mobile learning through its utilization of programs towards audience in Africa. This paper argues the best possible approaches aiming to enhance MOOC activities in Africa through the involvement of social networks.