Sven Manske

Towards an Online Lab Portal for Inquiry-Based STEM Learning at School

Nowadays, the knowledge economy is growing rapidly. To sustain future growth, more well educated people in STEM science, technology, engineering and mathematics are needed. In the Go-Lab project we aim to motivate and orient students from an early age on to study STEM fields in their future educational path by applying inquiry learning using online labs. This paper presents an inquiry learning portal where teachers can discover, use and enhance online labs appropriate for their courses and students can acquire scientific methodology skills while doing experiments using the labs. The Go-Lab portal architecture is presented, which contains a repository of online labs, inquiry learning spaces and complementary services. The paper discusses a first version of the portal and our future plans.

A Flexible and Extendable Learning Analytics Infrastructure

Currently architectures for learning analytics infrastructures are being developed in different contexts. While some approaches are designed for specific types of learning environments like learning management systems (LMS) or are restricted to specific analysis tasks, general solutions for learning analytics infrastructures are still underrepresented in current research. This paper describes the design of a flexible and extendable architecture for a learning analytics infrastructure which incorporates different analytics aspects such as data storage, feedback mechanisms, and analysis algorithms. The described infrastructure relies on loosely coupled software agents that can perform different analytics task independently. Hence, it is possible to extend the analytic functionality by just adding new agent components. Furthermore, it is possible for existing analytics systems to access data and use infrastructure components as a service. As a case study, this paper describes the application of the proposed infrastructure as part of the learning analytics services in a large scale web-based platform for inquiry-based learning with online laboratories.

AngeLA: Putting the teacher in control of student privacy in the online classroom

Learning analytics (LA) is often considered as a means to improve learning and learning environments by measuring student behaviour, analysing the tracked data and acting upon the results. The use of LA tools implies recording and processing of student activities conducted on software platforms. This paper proposes a flexible, contextual and intuitive way to provide the teacher with full control over student activity tracking in online learning environments. We call this approach AngeLA, inspired by an angel guarding over LA privacy. AngeLA mimics in a virtual space the privacy control mechanism that works well in a physical room: if a person is present in a room, she is able to observe all activities happening in the room. AngeLA serves two main purposes: (1) it increases the awareness of teachers about the activity tracking and (2) provides an intuitive way to manage the activity tracking permissions. This approach can be applied to various learning environments and social media platforms. We have implemented AngeLA in Graasp, a social platform that fosters collaborative activities.

“From Making to Learning”: introducing Dev Camps as an educational paradigm for Re-inventing Problem-based Learning

Dev Camps are events that enable participants to tackle challenges using software tools and different kinds of hardware devices in collaborative project-style activities. The participants conceptualize and develop their solutions in a self-directed way, involving technical, organizational and social skills. In this sense, they are autonomous producers or “makers”. The Dev Camp activity format resonates with skills such as communication, critical thinking, creativity, decision-making and planning and can be considered as a bridge between education and industry. In this paper we present and analyse our experience from a series of such events that were co-organized between an industrial partner acting as a host and several university partners. We take this as an indication to envision new opportunities for project-based learning in more formal educational scenarios.

Automated Indicators to Assess the Creativity of Solutions to Programming Exercises

Computer programs are a specific type of knowledge artefacts that result from a creative process under strong formal restrictions. From an educational perspective, it has been argued that programming supports intellectual development and knowledge building. In this paper, we give a short overview of a system created to automatically detect the creativity of solutions to programming exercises that address general mathematical and algorithmic skills. A first step to make these artefacts susceptible to automatic analysis was the definition a descriptive feature set that captures both structural and procedural aspects of each solution. Secondly, machine learning techniques have been used to form higher-level metrics simulating expert judgments on a given set of solutions. It turned out that expert judgments of program creativity differ considerably and systematically. This also led to a classification of the experts.

Correction to: “From Making to Learning”: introducing Dev Camps as an educational paradigm for Re-inventing Project-based Learning

CorrectionAfter the publication of this work [1] an error was noticed in the title of the article. The title in the original article reads: “From Making to Learning”: introducing Dev Camps as an educational paradigm for Re-inventing Problem-based Learning. However the correct article title should read: “From Making to Learning”: introducing Dev camps as an educational paradigm for Re-inventing Project-based Learning. This has been corrected here.

Predictive Knowledge Modeling in Collaborative Inquiry Learning Scenarios

The ongoing EU project Go-Lab provides a generalized interface and tool set to enable and structure learning activities with online laboratories. In this context, we have studied collaborative inquiry learning activities using various tools in blended learning scenarios. Former research indicates that the composition of heterogeneous vs. homogeneous groups in terms of student competencies or skills has an effect on the learning gain. This has been investigated using a theory-driven approach for predictive modeling based on Markov logic with data from a recent classroom study.