Cutting-edge Technologies for Analyzing Student Feedback to Inform Institutional Decision-making in Higher Education

Decision-making in higher education institutions faces complex challenges due to increasing data, regulatory demands, resource management, and changing educational needs. Effective decisions require accurate, timely insights into institutional processes. This study introduces an integrated decision-support approach consisting of Learning Analytics, Digital Twins, and Generative Artificial Intelligence (AI) with Retrieval-Augmented Generation (RAG). The objective is to enhance decision accuracy and operational efficiency in higher education. Learning Analytics provide insights into student performance, teaching effectiveness, and curriculum efficiency. Generative AI with RAG facilitates rapid retrieval and synthesis of institutional documentation and regulatory framework, enhancing decision accuracy. Digital Twins simulate institutional operations, enabling predictive resource planning and infrastructure modeling. Preliminary results indicate significant improvements in strategic planning and resource management by using an integrated decision support approach. Collectively, these technologies transform strategic decision-making and efficiency in higher education, enabling an agile and smart approach, offering a robust solution to contemporary challenges.

The purpose of this paper is to critically evaluate Archer’s reflexive modalities in relation to Further Education (FE) students’ higher education (HE) decision-making and choices. To do this, it draws on data from a qualitative, longitudinal narrative inquiry that explored how socioeconomically under-represented FE students made their HE decisions and choices. On a conceptual level, the research aimed to identify whether participants’ HE decisions and choices were individualised or mediated by structure. Margaret Archer’s reflexive modes were adapted to understand, first, how young people made their educational choices and decisions and, second, what role agency and structure played in this process. How participants’ different reflexive modes were interpreted and how this facilitated more intricate understandings of how agency is exerted in the face of structural constraints are discussed. Yet, this paper also critically reflects on and questions the explanatory power of Archer’s work in the context of this research.

The field of data analytics has seen substantial growth, particularly within the education sector. With the recent expansion of e-learning due to the COVID-19 pandemic, the ability to make data-driven decisions in education has become more important than ever. This review synthesizes existing research on the role of data analytics in enhancing academic performance and decision-making in higher education. The key objectives are to examine the influence of data analytics on student performance, explore learning analytics’ role in institutional decision-making, and assess the effect of data analytics on e-learning systems, particularly during the COVID-19 pandemic. Keywords: Academic Performance, Adaptive Learning Systems, Data Analytics, E-Learning, Higher Education, Learning Analytics, Student Engagement

Student Evaluations of Teaching (SET) are ubiquitous in higher education. They were initially designed as a tool to enhance teaching quality, but their use has, over time, shifted towards administrative use, sparking a debate on their effectiveness and fairness. This study examines the evolution of academic discourse on SET by conducting a bibliometric and sentiment analysis of 726 peer-reviewed articles published between 1950 and 2024. Articles were classified into three sentiment groups, positive, negative, and neutral/mixed, with the aim of mapping trends and thematic focuses within the literature. The findings indicate a trend towards negative publications and a divide between the positive and negative discourse, with limited overlap in references between the two. Positive articles focus primarily on measurement validity and SET’s role in improving teaching, while negative articles highlight biases, particularly gender bias, and concerns about the summative administrative use of SET rather than teaching quality. The shift towards negative publications has also occurred at the same time as the administrative use of SET has become institutionalised. Future research should explore ways to integrate formative SET practices to improve teaching quality while also addressing concerns about bias and fairness in faculty assessments.

Despite the increasing number of non-traditional students entering higher education (HE) in England, HE choices remain stratified by social class. Mature working class students are a target group of the widening participation policy, yet little attention has been given to their HE choices and decision-making. Through narrative inquiry, this study uses a creative method alongside focus groups and semi-structured interviews, and contributes a class perspective to the HE decision-making for 13 women on an Access to HE course. It links sociological theory to adult education, through a Bourdieusian framework. It evidences structural constraints and perceptions of belonging that impeded choices. A sense of place and feelings of fit (habitus) were significant for destination decisions. However, Access to HE course teachers were positively influential in helping students challenge embedded habitual ways of thinking and practice and in raising self-efficacy. The findings offer explanations as to why participation rates may be increasing but not widening enough. It illuminates how social class differences (intersected by age and gender) are crucial to understanding HE decision-making and places a much-needed focus on mature students to the widening participation and social mobility agenda.

The author has nearly 50 years of an academic career within the University of Bucharest. Over time, the author's academic activity has been heavily influenced by remarkable personalities from the university (especially the former Rector Ioan Mihailescu) or by world-class personalities (mainly Ken Robinson, John Naisbitt and Steve Jobs). Even if this career includes a valuable teaching and learning experience... it is approaching the "end of life". This article might be considered as a retrospective of the author's teaching activity and a chance to summarize the lessons he learned. These lessons could be seen as recommendations for the academic staff and the decision makers in higher education. The article contains two important chapters. Over time, the author's academic activity has been heavily influenced by remarkable personalities from the university (especially the former Rector Ioan Mihailescu) or by world-class personalities (mainly Ken Robinson, John Naisbitt and Steve Jobs). Even if this career includes a valuable teaching and learning experience... it is approaching the "end of life". This article might be considered as a retrospective of the author's teaching activity and a chance to summarize the lessons he learned. These lessons could be seen as recommendations for the academic staff and the decision makers in higher education. The article contains two important chapters. Chapter 1 has the title "Innovative teaching in higher education". Innovation is essential for the permanent and sustainable success of any person /organization. This chapter presents some general aspects related to education worldwide and some specific aspects related to the author's academic initiatives. As soon as these initiatives have been implemented for the first time in the University of Bucharest, they can be characterized as being innovative for the education system of this institution. Many of these achievements were reported during international and national conferences. Chapter 2 has the title "Disruptive technologies with a strong impact on higher education". The author has taken into account the potential of digital technologies for higher education since 1990. The essential moment was the reading of the book "Megatrends," published by John Naisbitt in 1982, having as the main message the movement from the industrial society to the information society. Chapter 2 summarizes some of the best practices on the use of digital technologies in higher education, including cloud computing, learning management system, eLearning, game-based learning. Finally, the article includes conclusions and references itself.

Research use in educational decision-making has been encouraged and well documented at the K-12 education level in the United States but not in higher education, or more specifically for educational technology. We conducted a qualitative study to investigate the role of research in decisions about acquiring and using educational technology for teaching and learning in higher education. Results from 45 interviews of decision-makers in higher education show that they engage in different types of research activities throughout the decision-making process, but that in most cases the research is lacking in methodological rigor. Externally-produced, scientifically-rigorous research was mentioned in less than 20% of interviews. Decision-makers often conduct their own internal investigations on educational technology products and strategies producing locally-relevant, but usually less-than rigorous, evidence to inform decisions about continuing use of the technology or scaling up.

This chapter critically reflects on the use of the event-based diary method in capturing accounts of higher education (HE) decision-making and choices among student choosers. These reflections focus on ‘reactivity’, how this can overshadow the role of emotion in decision-making and choice processes, the suitability of diaries for capturing complexity in these processes, and finally, ethical questions concerning how diarising decisions and choices may impact participants’ well-being and perceptions of the self. To guide these reflections, the chapter uses data from an Economic and Social Research Council (ESRC) funded study which explored the HE decision-making and choice journeys of Further Education (FE) students in England between 2014–2015. In doing so, a case is made for the potential value of the event-based diary method in future HE research, including studies focusing on: macro-micro relationships, aspirations and transitions, and explorations of student and/or staff experiences of HE cultures and environments.

Various academic institutions in higher education (HE) allocate their resources differently to improve the quality of teaching and learning. To measure and identify the teaching and learning quality in any educational context, institution performance in this field must be evaluated using different techniques and instruments, one of which is Student Evaluation of Teaching (SET). The study aims to determine the use of SET to improve teaching quality based on the opinions of teachers (n = 6) and students (n = 413). This is achieved by investigating 1) the degree of alignment or divergence between teachers’ and students’ ratings of a particular course, 2) how teachers value students’ feedback on teaching to improve their teaching practises, 3) students’ perspectives on using SET in improving teaching quality and 4) the implications for implementing SET effectively in HE context. These were addressed using an adapted version of the Students’ Course Evaluation Questionnaire (SCEQ), and the Mann-Whitney test was used to analyse the data. The findings reveal a statistically significant correlation coefficient (r = 0.739) between teachers’ and students’ evaluations. The associated p-value (0.058) is slightly greater than the conventional threshold of p ≤ 0.05. The results of the Mann-Whitney U test indicated an overall concurrence between teachers’ and students’ evaluations, although certain inconsistencies were observed. The findings indicate a consensus among teachers and students regarding SET’s efficacy in enhancing instructional quality.

Given higher education in Morocco suffers from the increasing number of students in institutions with open access policy, the issue of language and communication, the heterogeneous academic level of students, the inability to adapt schedules for students, the evolution of new technologies, etc., innovative pedagogy has become a necessity to address these challenges. Additionally, new modes of adaptive learning need to be designed to develop innovative training programs. Many authors agree that “innovation in pedagogy concerns everything that is not part of formal education” (Lison et al. 2014). In 2016, the Ministry of National Education, Vocational Training, Higher Education and Scientific Research in collaboration with GIP FUN MOOC, and the French Embassy signed an agreement to establish a platform MUN “Morocco Digital University”. The purpose of the agreement is to encourage Moroccan Universities to develop Massive Open Online Courses (MOOCs), Small Private Online Courses (SPOCs), and other forms of online courses and to reinforce partnership with French Universities in e-learning. MOOCs were developed in 2008, and after four years of operation, the New York Times considered 2012 “The year of the MOOC”. Since then, new features of MOOCs have motivated decision makers in higher education from across the world to create a number of online courses in their institutions. However, the weakness of MOOCs as a pedagogical innovation is the high dropout rate. Despite being massive courses, of thousands of enrollees, 50% quit after one week, 10% finish the course after completing all the modules, and only 4% obtain a certificate (Perna et al, Life Cycle of a Million MOOC Users. MOOC Research Initiative. Arlington, Texas, 2013). Given MOOCs are large-scale learning platforms that have failed to meet learners’ individual needs, considering this innovative pedagogy effective enough is conditional on adapting instruction to enhance student learning, learner’s characteristics, for example, knowledge or personal interests. In fact, why not implement adaptive learning techniques to further customize MOOCs? The purpose of this study is twofold. First, it aims to uncover the feasibility of adaptive learning on MOOCs in higher education in Morocco. Second, this investigation seeks to address the effects of adaptive learning on student learning outcomes, student engagement, and drop-out rates.

The use of algorithms for decision-making in higher education is steadily growing, promising cost-savings to institutions and personalized service for students but also raising ethical challenges around surveillance, fairness, and interpretation of data. To address the lack of systematic understanding of how these algorithms are currently designed, we reviewed an extensive corpus of papers proposing algorithms for decision-making in higher education. We categorized them based on input data, computational method, and target outcome, and then investigated the interrelations of these factors with the application of human-centered lenses: theoretical, participatory, or speculative design. We found that the models are trending towards deep learning, and increased use of student personal data and protected attributes, with the target scope expanding towards automated decisions. However, despite the associated decrease in interpretability and explainability, current development predominantly fails to incorporate human-centered lenses. We discuss the challenges with these trends and advocate for a human-centered approach.

In the socio-technical imaginary of higher education, algorithmic decision-making offers huge potential, but we also cannot deny the risks and ethical concerns. In fleeing from Frankenstein’s monster, there is a real possibility that we will meet Kafka on our path, and not find our way out of the maze of ethical considerations in the nexus between human and nonhuman agencies. In this conceptual article, I map seven dimensions of student surveillance on an experimental matrix of human-algorithmic interaction to consider some of the ethical implications of algorithmic decision-making in higher education. The experimental matrix of human-algorithmic decision-making uses the four tasks of ‘sensing’, ‘processing’, ‘acting’ and ‘learning’ to open up algorithmic-human agency as comprising a number of possibilities such as (1) where only humans perform the task; (2) where the task is shared between humans and algorithms; (3) where algorithms perform the task but with humans supervising; and (4) where algorithms perform the tasks with no human oversight. I use this matrix to engage with seven dimensions of how higher education institutions collect, analyse and use student data namely (1) automation; (2) visibility; (3) directionality; (4) assemblage; (5) temporality; (6) sorting; and (7) structuring. The article concludes by proposing a number of pointers to be taken into consideration when implementing algorithms in a higher education context from a position of an ethics of care.

This paper will examine the development of a data warehouse aimed at improving decision-making in higher education, which focuses on the identification of students at-risk of academic failure through machine learning techniques. This research utilizes South East European University (SEEU) as a case study to show how data warehousing can integrate various student data—including demographics, academic performance, grades, attendance, and engagement—into an integrated framework that enables predictive analytics. The overall approach allows SEEU decision-makers, administrators, and faculty to proactively identify and assist at-risk students, which improves student retention and their academic success. The results underscore the crucial role of data warehousing in enhancing student achievement and facilitating informed decision-making in higher education. The paper concludes with concrete suggestions for leveraging data to enhance decision-making processes in a digital educational institution.

Decision-making is demanding, especially when referring to strategic decisions. The higher education sector and its institutions are specific in their three main pillars: education, research and knowledge transfer (i.e. contribution to society), which are different to the priorities of a typical business/corporate environment. This makes strategic decisionmaking and implementation in higher education even more demanding. No matter how sound it is, a strategic decision is not successful if its implementation is unsuccessful, inadequate or of poor quality. As the basis for defining and assessing ability to implement a strategic decision the maturity model for a strategy (decision) implementation may be used. The maturity model is a theoretical model by which the guidelines are given to organizations or institutions about how their abilities can be transformed from the initial levels to the desired level of maturity in some (key) areas. The paper describes the capability maturity model as the basis for the development of the methodology for monitoring the implementation of strategic decisions in higher education (institutions) as one of its key success factors.

In this paper, I call attention to the problem of continuing to rely on SETs for hiring, reappointment, promotion, and award decisions in higher education, including the problem of continuing to permit the use of SETs despite the clear and explicit acknowledgement of their shortcomings. I argue that to do so manifests a failure to acknowledge the weight of the actual and potential harms of SETs. I then provide an outline of such harms in order to clearly convey not only the weight but also the extent of such harms, especially on marginalized job candidates and non-privileged students. I also report the results of a recent survey I conducted in order to document any actual or possible harms that were committed against professional educators by the use of SETs in hiring, reappointment, or promotion decisions. I conclude by arguing that, given all of the foregoing, the use of SETs should be abolished for hiring, reappointment, promotion, and award decisions in higher education.