The institutional adoption of learning analytics in the Netherlands is still low. This chapter presents a study on the challenges that Dutch higher educational institutions encounter when adopting learning analytics. The literature describes possible challenges regarding assets, data governance, data literacy, data quality, organizational culture, pedagogical grounding, privacy and ethics, and technical issues. Eight interviews with practitioners from four universities verified that all these challenges are causing problems for Dutch institutions as well. The practitioners provided recommendations on how to overcome these adoption challenges. Higher educational institutions need to demonstrate the value of learning analytics, provide users with training, clearly identify users' needs, and establish a ‘one-stop-shop' that acts as a single contact point within the organization. Combined with recommendations already present in the literature, this helps accelerate the successful adoption of learning analytics by Dutch higher educational institutions.
TopIntroduction
Learning analytics has emerged as a powerful tool for higher educational institutions to gather and analyze learner data to optimize learning and learning environments. Learners generate vast amounts of data by interacting with learning management systems, digital resources, and educational applications. Especially during the Covid-19-pandemic, higher educational institutions adopted digital technologies for educational purposes, increasing the number of potential learner data sources. The analysis of these data provides valuable insights into student learning behaviors, preferences, and performance. This process is called learning analytics.
Learning analytics’ main groups of potential users are learners and educators (Romero & Ventura, 2020). Learning analytics benefit learners as it enables personalized learning, provides them with insights into their learning processes and progress, and offers adaptive and engaging learning experiences. Educators benefit from information that allows them to perform targeted interventions, make informed instructional decisions, adapt teaching strategies, and evaluate curriculum effectiveness. Learning analytics can also reduce the instructors’ workload via automated grading and by providing automated feedback to learners.
Many higher educational institutions want to reap the benefits that learning analytics provides. However, many institutions struggle to adopt learning analytics at scale (Tsai & Gašević, 2017; Viberg, Hatakka, Bälter, & Mavroudi, 2018). Institutions face different challenges when adopting and implementing learning analytics in their educational practices. From a pedagogical point of view, Baker (2019) mentions problems relating to transferability, effectiveness, interpretability, applicability, and generalizability. From an organizational perspective, there are challenges regarding the purpose and gain, policies, transparent communication, privacy, and ethics (Leitner, Ebner, & Ebner, 2019). So, adopting learning analytics is a complex undertaking, that requires attention to many different aspects.
Learning analytics adoption is studied by many researchers. However, much literature on learning analytics adoption and its challenges originates from North America, the United Kingdom, and Australia (Yau & Ifenthaler, 2020). This raises the question of whether the same challenges and solutions apply to educational systems in other geographical regions and countries. For example, due to the General Data Protection Regulation (GDPR), educational institutions in Europe might face specific challenges regarding learners’ privacy. In this study, we focus on the challenges that Dutch higher educational institutions encounter. Dutch instructors have high expectations regarding the use of learner data to better understand learning activities, provide feedback to learners, and adapt the curriculum to meet learners’ needs (Kollom et al., 2021). However, anecdotic evidence shows that most Dutch institutions momentarily only employ small-scale initiatives (Stolk, 2022). Recently, an eight-year national program called ‘NPuls’ started. In this program, with a EUR 560 million budget, over one hundred institutions work together on innovative themes, including learning analytics (Npuls, 2023). To enable the program to reach its full potential, it is crucial to investigate what is holding Dutch higher educational institutions back from adopting learning analytics. Therefore, we aim to identify what challenges Dutch higher educational institutions might face when adopting learning analytics. Moreover, we research what solutions are already known to overcome these challenges.
Our study answers the research question “What challenges do Dutch higher educational institutions face when adopting learning analytics and how to overcome these challenges?” The challenges and potential solutions are identified via a literature review and semi-structured interviews with eight employees from four different Dutch higher educational institutions. Each interviewee has experience with learning analytics, either from an educational or a technical perspective.