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Automatic scoring and feedback tools have become critical components of online learning proliferation. These tools range from multiple-choice questions to grading essays using machine learning (ML). Learning environments such as massive open online courses (MOOCs) would not be possible without them. The usage of this mechanism has brought many exciting areas of study, from the design of questions to the ML grading tools' precision and accuracy. This paper analyzes the findings of 125 studies published in journals and proceedings between 2016 and 2020 on the usages of automatic scoring and feedback as a learning tool. This analysis gives an overview of the trends, challenges, and open questions in this research area. The results indicate that automatic scoring and feedback have many advantages. The most important benefits include enabling scaling the number of students without adding a proportional number of instructors, improving the student experience by reducing the time between submission grading and feedback, and removing bias in scoring. On the other hand, these technologies have some drawbacks. The main problem is creating a disincentive to develop innovative answers that do not match the expected one or have not been considered when preparing the problem. Another drawback is potentially training the student to answer the question instead of learning the concepts. With this, given the existence of a correct answer, such an answer could be leaked to the internet, making it easier for students to avoid solving the problem. Overall, each of these drawbacks presents an opportunity to look at ways to improve technologies to use these tools to provide a better learning experience to students. © 2013 IEEE.

Students’ acquisition of generic skills is a key to their incorporation into the job world. However, teachers encounter several difficulties when measuring their students’ performance in generic skills. These difficulties increase in online courses based on learning management systems, where there is no direct contact between teachers and their students. To address this problem, this paper adopts a solution based on the use of activity records from learning management systems as indicators of the students’ performance in generic skills. After conducting a survey among teachers of online courses on the suitability of the solution, an artefact was developed and applied within four online courses. Interviews conducted with teachers and the results of a survey for mapping skills and activities provide positive evidence of this solution’s potential.

This chapter presents a proposal for a pattern-based approach for Computer Supported Collaborative Learning (CSCL) scripts that aims to integrate learning and assessment activities. After a general presentation of the approach, the chapter will focus on a case study which covers the whole life-cycle of a CSCL script with embedded assessment activities. The case, which took place in the context of a computer-mediated learning environment, includes the design, instantiation, enactment and evaluation of the script. Focusing on the relevance of the assessment activities which are integrated in the script, the case study illustrates the complexity of formalizing computer-interpretable CSCL scripts with embedded assessment. The usage of design patterns is proposed as a means of providing support and hiding the complexity of creating and enacting such scripts. The case study shows the feasibility of this approach, and provides information about the requirements of CSCL script authoring tools to employ assessment and learning design patterns to support non-expert designers in those tasks.

Proceedings of: 2nd International Conference on Intelligent Networking and Collaborative Systems (INCOS 2010): Second International Workshop on Adaptive Systems for Collaborative Learning (IWASCL-2010). Thessaloniki, Greece, 24‐26 November, 2010. The introduction of portable devices in education opens up new possibilities for Computer Supported Collaborative Learning by providing advanced learning scenarios with activities in different spatial locations. However, organizing and structuring collaborative learning adaptive flows in these innovative scenarios represents also a workload for practitioners, which hinder the adoption of these technologies. As a step forward to alleviate this workload, this paper analyzes the limitations and bottlenecks detected in an actual collaborative blended learning experience carried out in a previous study and proposes a technological solution for solving them. The resulting solution is presented as a concept proof consisting of a Unit of Learning suitable to be instantiated with IMS Learning Design and complemented by a Generic Service Integration system. The paper also discusses to which extent the proposed solution covers the limitations detected in the previous study and how useful could be for reducing the orchestration effort in future experiences. This work has been partially funded by the Project Learn3 (TIN2008-05163/TSI) from the Plan Nacional I+D+I, the Spanish National Project FLEXO (TSI-020301-2008-19, www.ines.org.es/flexo) and "Investigación y Desarrollo de Tecnologías para el e-Learning en la Comunidad de Madrid” funded by the Madrid Regional Government under grant No. S2009/TIC-1650. Publicado