This systematic review critically evaluates the nexus between data-driven design (DDD) and design processes (DP), guided by PRISMA standards. It synthesises findings from 84 selected articles from databases such as WoS and Scopus, published between 2010 and 2023. It identifies a notable gap in the literature in directly linking DDD to DP, while acknowledging a broader, more complex relationship. This research reveals the complexity of integrating DDD into traditional design paradigms, highlighting both challenges and opportunities for innovation. The findings serve as an important resource for academics and practitioners interested in using data to enhance DP. As well as highlighting existing challenges and opportunities, the review calls for further research to fill identified gaps, highlighting the significant potential for advancing design methodologies through a more coherent integration of data-driven insights. This work points to the need for a deeper understanding and use of DDD to improve traditional design practices.

Online courses heavily relying on programming skills tend to be difficult and time-consuming for students, who may get frustrated when stuck in an assignment. Obviously, this may increase drop-out rate and decrease academic performance as well as students’ satisfaction with the course and the institution in general. In this context, we propose a notification, recommendation and monitoring system which is integrated into an automatic assessment tool with the aim to enhance the learning process in virtual classrooms. In particular, notifications, recommendations and visualization reports are used to show the activity, progress and performance of all students. The system is implemented in a distributed computing course in an online university. A quantitative analysis method used to collect and analyze data of students’ perceptions regarding the system showed that: (1) notifications helped students organize their time and encourage them to work more effectively; (2) recommendations allowed students to receive useful and timely scaffolding for coping with their problems and completing their assignment; and (3) visualization reports provided valuable insights toward monitoring the learning process. Moreover, the analysis of correlations showed that the reception of recommendations and the visualization reports is related to encourage students to do more executions and to start earlier the assignments. Finally, this study seeks to contribute to online teachers’ endeavor to enhance students’ engagement, performance and learning in the field of programming (and not only).

This paper presents a technology-enhanced assessment system that can be used for both skill and knowledge learning. For this purpose, a general technology-enhanced assessment system is designed and developed for an online logic course at a fully online university, taking into account e-learning standards and specifications, which can be easily adapted to any institute and subject requiring a high level of skill learning. Through this system, both learning and formative assessment facilities are provided to students. To evaluate its effects on student learning process, the system is applied in a real logic course at the Universitat Oberta de Catalunya (UOC). Based on the evaluation, it shows that students� are more engaged with the system and, as a result, their performance in the subject had improved. Also, based on the feedback obtained through the evaluation, it shows that students are satisfied with the facilities and assessments provided by the system. Overall, the introduction of the technology-enhanced assessment system for skill and knowledge learning has yielded some interesting results.

This paper presents an architecture for a technology-enhanced assessment system for assessing both skill and knowledge acquisition in online higher education while adhering to standards and specifications. This technological requirement is achieved through designing a system which allows the integration of existing partially effective tools with common Learning Management Systems (LMSs) according to standard conformance. The system is designed and developed in a way that it can be used as modules to existing systems or LMSs.

In this paper, we describe the navigational behavior of the students of an e-learning virtual environment, in order to determine whether such navigational patterns are related to the academic performance achieved by the students or not, and which behaviors can be identified as more successful. As an example, a subset of students taking a degree in computer science in a completely virtual online university is selected as the matter of study. Three levels of analysis are described: a session level, where students perform a few actions in a single session logged to the virtual campus; a course level, where all single sessions are joined to form a course navigational pattern; and a lifelong learning level, where students enroll in several subjects each academic semester. A simple experiment is outlined for the course level to demonstrate the possibilities of such analysis in a virtual e-learning environment. This experiment shows that the information collected in this level is useful for understanding user behavior and the relationship with his or her academic achievements, and that some intuitive ideas about the relevance of specific user actions or particularities can be also better explained.