The Question at the Heart of Assessment in Higher Education: Are We Assessing for Competency Acquisition?

Abstract

European universities are increasingly adopting competency-based education to enhance transfer between academic and professional contexts, demanding assessment systems aligned with classroom practices. This study explores what is assessed in three Spanish universities. Spain constitutes a particularly relevant case: its course guides are legally binding contracts subject to external audit by the National Agency for Quality Assessment and Accreditation (ANECA), ensuring exceptional standardization. A theory-driven documentary analysis examined 7810 teaching guides from all degree programs, with coding supported by ATLAS.ti software applied to these documents, which represent statements of intent by faculty members. The findings reveal notable discrepancies: competencies were rarely the central focus of assessment, and evaluation appeared fragmented, overlooking the integration of knowledge, skills, and attitudes. These gaps raise concerns about the innovative dimension of competency-based models. The study concludes that institutional assessment schemes should promote holistic education, ensuring students develop collaborative and cross-disciplinary capacities essential for professional environments.

1. Introduction

In recent years, the European Skills Agenda and the Organisation for Economic Co-operation and Development (OECD), among others, have emphasised the importance of a competency-based learning model as a means of fostering societal progress and addressing the challenges of an ever-changing world [1,2]. This model serves as a guide for university teaching by integrating knowledge, skills and attitudes to solve complex problems in real-life contexts, as well as promoting transfer between the academic, personal and professional spheres [3]. An innovative assessment system is therefore required that is consistent with the educational approach used in the classroom. This translates into assessment schemes focused on students’ all-round development [4,5], which evaluates their ability to apply the knowledge acquired in contextualised, authentic, real-life situations. Furthermore, this competency-based learning model should support teachers in identifying key aspects of the assessment process that encourage learning [6,7] and are formative in nature [8,9]. They should also take into account different instruments for collecting information on students’ competency achievements (knowledge, skills and attitudes), which do not merely play a certifying role, but make a contribution to the improvement of students’ education. Ultimately, it should assess the innovative dimension of higher education teaching [10].

This shows that assessment is an essential component of the learning process in higher education. This is because it not only allows the knowledge acquired by students to be measured, but also serves as an educational tool that guides and enhances learning [11]. Moreover, it has an essential role in improving education quality, the development of meaningful learning and the institutional responsibility of universities and public administrations [1]. Yet it remains unclear whether these principles are effectively translated into actual assessment practice in higher education institutions—that is, whether what is being assessed in the classroom genuinely reflects the demands of a competency-based model.

Research on assessment in the learning process and competency acquisition in higher education is critical to improve the effectiveness of academic university programmes [12,13]. From this perspective, it cannot be ignored that assessment, through its formative function, also contributes to achieving an objective established by international policies and regulations—namely Sustainable Development Goal 4 of the 2030 Agenda [14]. Research on assessment therefore contributes to advancing quality education [15].

Despite growing recognition of the importance of competency-based assessment, empirical evidence on what is actually assessed in university teaching guides remains scarce. No study has yet systematically examined, at scale, whether the constituent elements of competencies are reflected in the assessment schemes encoded in institutional documentation across multiple universities and disciplines. The present study addresses this gap by analysing 7810 teaching guides from three Spanish universities in order to determine whether competency-based learning is genuinely taken into account in assessment design.

1.1. The Study

The study presented in this article is part of the multi-centre research project entitled ‘Institutional Leadership for the Assessment of Student Competencies and the Development of University Engagement’ (LIECEDEU; PID2022-136372NB-I00), funded by the Spanish State Research Agency, the Ministry of Science, Innovation and Universities, and co-funded by the European Union. Furthermore, this research was approved by the Ethics Committee of the University of Murcia (Ref. 4267/2023), thus ensuring compliance with ethical principles, and was carried out jointly by the University of Murcia (UMU), the University of Santiago de Compostela (USC) and the University of Cordoba (UC), Spain. The main objective of the project is to identify, describe, analyse and interpret the institutional conditions that influence the learning and well-being of university students, with special emphasis on assessment practices and their relationship to organisational dynamics.

The research addresses two levels of institutional architecture—organisational management and pedagogical management—structured around four dimensions of analysis: (1) institutional leadership, encompassing the processes and decisions undertaken by the vice-chancellor’s office, dean’s office and department teams; (2) implementation of the Competency-Based Education (CBE) model, adopted in the context of the European Higher Education Area (EHEA); (3) student assessment practices, which constitute the core focus of this study; and (4) engagement of the university student body, understood as active participation in learning, a sense of belonging to the institution and satisfaction with their academic experience. This research used a mixed-methods approach to find out whether the dimensions studied exhibited internal coherence and how they influenced each other.

Within the theoretical framework of assessment theory, this study aims to analyse what is being assessed by using the teaching guides from all undergraduate degree programmes at the three participating universities in order to determine whether competency-based learning is taken into account. These official and public documents detail the planning, content, methodology, competencies, and assessment system of a university course. The adoption of this common format facilitates comparison between the different elements that comprise it, namely, identifying information about the course, such as its nature, number of credits, estimated workload, etc., and information about the teaching staff, including their names, departments, email addresses, etc. These elements also include the presentation of the course: admission requirements (incompatibilities, requirements and recommendations), competencies to be developed, content, learning activities, assessment system (instruments, assessment criteria, what is assessed and weighting), learning outcomes, and bibliography. The different teaching guides yield information about the intentions formulated by teachers for the corresponding academic year. Moreover, by examining the structured learning pathways of the various subjects within university degrees—framed by their respective curricula—it was possible to readily identify the focus of lecturers’ assessment; that is, the core areas around which student assessment was centered. This reflected various aspects, including the culture of the university in question [16,17]. These sources have previously researched in order to evaluate important issues, including teaching quality [18]; teaching guidelines and positioning [19]; the gender approach [20]; the role of women [21]; and knowledge construction [22], among others.

Specifically, this study is guided by the following research questions:

• RQ1: What aspects of student learning are most commonly identified as the object of assessment in the teaching guides of three Spanish universities?
• RQ2: To what extent do teaching guides reflect the integration of the constituent elements of competencies (knowledge, know-how, know-how to be, and know-how to be around others) in assessment design?
• RQ3: Are there differences in assessment focus across universities, areas of knowledge, and subject types?

1.2. Background

In Europe, the competency-based model serves as the guiding framework for instructional practices within university classrooms [3]. This model conceives competencies as ways of knowledge, skills (practical abilities) and attitudes (values and behaviours) that are mobilised using an integrative approach in order to solve a complex problem in context. This definition highlights both the acquisition of theoretical knowledge and its application to real-life or quasi-real (socio-professional) situations, while also acknowledging the socio-emotional dimension [5]. University education is therefore expected to reinforce the connection between the academic, personal and professional domains, enabling students to transfer their learning to other contexts and address complex problems in a practical, reflective and critical way [23]. Assessment not only measures the degree to which students have acquired and applied this knowledge but also provides an overall view of their learning [24]. Thus, the importance of assessing transferable competencies has been recognised, together with the way in which students are assessed and prepared to face the challenges of the professional world. These principles have been promoted in European universities by initiatives such as the Tuning Project and the European Qualifications Framework [25].

Accordingly, in terms of research, the assessment of competencies at university has been polarised between two focal points, that is, two ways of understanding initial education. One focus has been based on a technical conception, primarily linked to and oriented towards professional qualifications, student employability and system productivity; the other has been aimed at ensuring the all-round development of students [24,26].

The neoliberal perspective has been primarily centred on employability and professional training. Emphasis has been placed on the need for students to demonstrate their ability to apply what they have learned in practical settings that reflect the demands of the labour market. Studies have given priority to institutional strategies for students to acquire competencies in their degrees and how they meet labour market and employer needs [27]. Examples include the Tuning Project, which provides guidance for universities to adapt their educational programmes to the needs of the labour market, using competencies as assessment criteria [28].

From the point of view of all-round education, initial education is propaedeutic in nature, that is, it prepares students to face not only professional, but also academic and social challenges. In this respect, research has encompassed educational improvement, including the assessment of teaching competencies for student monitoring [29]; the assessment of digital competencies [30]; and the role of assessment in student dropout [31,32]. It is important to emphasise the role of universities as institutions that ‘are shifting from content-based curricula to competency-based curricula, through processes that require monitoring and assessment systems’ [3] (p. 9). However, the European Association for Quality Assurance in Higher Education [33], which provides European-level guidelines for internal and external quality in university programmes in the EHEA, has emphasised the assessment of how (the assessment process), while overlooking what, that is, the object of assessment.

In this regard research on university assessment in Spain has advanced significantly in the procedural dimension, with authors such as Ibarra-Sáiz et al. [34] analysing the means and instruments, or Cañadas [35] demonstrating the benefits of formative assessment. However, these studies tend to prioritise the instrument(s) or the function (formative vs. summative) of the process; there is therefore a less explored area: the substantive or content dimension. While the procedural dimensions (assessment tools) and the perceptions of the agents involved (students and teaching staff) have been extensively explored, the intrinsic nature of the objects of assessment—the what of assessment—remains an opaque dimension. It is therefore imperative to analyse course guides not merely as administrative documents, but as cognitive maps that define what knowledge is considered valuable in higher education.

It cannot be overlooked that Spain was one of the countries that underwent the most bureaucratized and regulated transition toward the European Higher Education Area (EHEA). Teaching programs—previously a list of topics that instructors covered in class—became course guides: a binding and legally enforceable contract between the university and the student. This contract obliges teaching staff to comply with its contents, and failure to do so constitutes a formal irregularity. Furthermore, and unlike more flexible systems where the syllabus is merely a statement of intent, Spanish universities are subject to strict oversight by the National Agency for Quality Assessment and Accreditation (ANECA), which reviews whether each course guide is aligned with the degree’s official Verification Report. In short, these official documents are subject to external audit, and consequently, the study of these guides makes it possible to analyze institutional traceability and coherence. Spain thus possesses one of the most structured and thoroughly documented quality assurance systems in Europe.

In short, regardless of the theoretical orientation in which it is situated, the literature has underscored the significance of competency-based assessment in fostering a broader and more contextually grounded approach to learning within the university setting. Studies have highlighted the importance of measuring ways of knowledge, skills (practical abilities) and attitudes (values and behaviours) as tools for enhancing educational quality and promoting student employability. But what is really happening in universities in Spain? What is being assessed? To address these questions, this study analyses what is assessed in the classrooms of three universities in Spain.

1.3. Theoretical Framework

The subject of this article is the assessment of student learning by competencies, based on the Theory of Student Assessment [36,37], which conceives of learning assessment, on the one hand, as a means of grading, focusing on the knowledge acquired, and, on the other hand, as a means of improving teaching processes when the expected achievements are not obtained in practice. In the current educational model, a Competency-Based Teaching Model, assessment is approached from a comprehensive perspective, evaluating the knowledge acquired by the student, their ability to use it [38] and an assessment for improvement [39], thus answering the question: what to assess? Following this competency-based model, assessment must integrate these four elements simultaneously:

(a)

Knowledge: the acquisition of concepts, theories, principles, data and facts. Without a knowledge base, there is no competence, but knowledge alone is not enough.

(b)

Skills: technical and practical ability to apply that knowledge in real or simulated situations: problem solving, decision making and task execution.

(c)

Attitude, values and behaviours: values, ethics and personal disposition. This determines how knowledge is used (with responsibility, empathy, proactivity, etc.).

(d)

Social interaction: focuses on the social and emotional competencies necessary to live and work in society. The ability to collaborate, respect others’ opinions, communicate effectively and resolve conflicts is assessed.

In short, it is a combination of cognitive skills (knowledge), practical skills (abilities, capacity to apply that knowledge in real situations) and emotional skills (social interaction; attitudes, values, etc.). This combination should be the benchmark for teacher assessment in education in relation to ‘what to assess’. Therefore, teachers must integrate these elements into their planning, ensuring that decisions made in relation to “what, how and when to teach” are consistent with decisions related to “what, how and when to assess” [39,40].

In addition to the above theoretical axes, this study situates itself within the evolving field of educational evaluation theory. Guba and Lincoln [41] identified four generations of evaluation practice—measurement, description, judgment, and pluralism—each defined by a shift in epistemological and methodological assumptions about the nature and purpose of evaluation. Building on this historical framework, Brousselle and Buregeya [42] proposed the emergence of a fifth generation—the “explanation generation”—grounded in theory-based approaches that seek to explain the mechanisms and contextual conditions behind observed outcomes, rather than merely describing or judging them. The present documentary analysis is consistent with this explanatory orientation: rather than simply cataloguing what assessment practices appear in teaching guides, it seeks to understand the extent to which institutional documentation reflects—or fails to reflect—the underlying logic of competency-based education.

2. Materials and Methods

The research used a theory-driven documentary analysis to examine student assessment schemes in the university context. This approach constitutes the documentary strand of the broader mixed-methods LIECEDEU project. It focused on how the assessment of learning outcomes was articulated in the teaching guides, and the ways in which these were taken as a framework for the regulations, guidelines and course syllabus. In short, how it was conceived and structured at the institutional level.

The central premise was to describe assessment practices as reflected in institutional documents [43,44]. This made it possible to grasp the complexities of institutional assessment approaches in the university environment by examining how they were encoded in official teaching guides. This documentary research perspective generated valuable qualitative data to answer the research questions and provide specific details on how the institutions under study apportion value to student assessment.

2.1. Design

Documentary research design is based on a systematic approach to information analysis. It focuses on the collection, analysis and interpretation of data, i.e., information already existing in documents, books, scholarly articles, reports and other written materials [43]. In this study, it was decided to analyse the teaching guides in order to meet the research objective. This type of approach is particularly useful for this kind of study, as in-depth analysis of primary data is needed to understand teachers’ assessment practices. The researcher systematically examines and analyses relevant sources to extract and synthesise information that is significant to the study.

In documentary research design, it is therefore essential to clearly define the research problem and formulate accurate questions to guide the search for information [44]. In addition, the critique and evaluation of sources is essential for ensuring the reliability and validity of the data. The researcher must develop rigorous criteria for selecting and analysing sources. The process adopted in this study involved a thorough review of publicly available teaching guides at the three participating universities to identify previous contributions to the object of the analysis.

As indicated in [43,44], this type of design requires that information collected be organised and categorised in the analysis phase in order to address the stated research questions and objectives. Furthermore, this may include the use of techniques whereby patterns and trends can be identified in the data. Interpretation of the findings should be careful and reflective in order to situate the results within the broader context of the field of study. Documentary research design not only provides an in-depth, contextualised understanding of the topic, but can also reveal new perspectives and areas for future research.

2.2. Data and Sample

An analysis of primary documents was first carried out. These documents were the teaching guides for all the degree courses of the three participating universities. Given that the preliminary screening would be assisted by analysis software, the methodological approach selected was a population-based study. Therefore, the data collected consisted of the 7810 teaching guides for each of the subjects of the degree courses of the universities participating in the project. One of the advantages of conducting the study in this way was the population coverage of the categories identified.

The search process was as follows:

• All course guides were collected from the universities’ websites.
• All course guides were imported into the ATLAS.ti software.
• Using the programme’s search tool, the software was instructed to identify where the key words (subcodes) used appeared in each of the documents (

  Table 1. Codes and their respective sub-codes used in the search.

  Code	2. What	3. Who/For Whom	4. Purpose	5. How
  Meaning	The aim is to identify what is being assessed	The aim is to identify who is carrying out the assessment and for whom	The aim is to identify the purpose of the assessment	The aim is to identify how the assessment is carried out
  Sub-codes	2.1. Skills 2.2. Thinking 2.3. Ability 2.4. Understanding 2.5. Team 2.6. Application 2.7. Performance 2.8. Practice 2.9. Adaptation 2.10. Values 2.11. Standards 2.12. Competencies 2.13. Quality 2.14. Learning 2.15. Progress 2.16. Results 2.17. Knowledge 2.18. Commitment 2.19. Resources	3.1. Peers 3.2. Self-assessment 3.3. Collaborative	4.1. Assessment for… 4.2. Integration 4.3. Knowledge 4.4. Needs 4.5. Learning 4.6. Understanding 4.7. Inclusive 4.8. Development 4.9. Holistic 4.10. Purpose 4.11. Application 4.12. Transfer 4.13. Practice 4.14. Professional 4.15. Improvement 4.16. Autonomy 4.17. Responsibility 4.18. Training 4.19. Accreditation 4.20. Classification 4.21. Employment 4.22. Selection 4.23. Assistance	5.1. Integrated 5.2. Process 5.3. Criteria 5.4. Importance 5.5. By means of 5.6. Instruments 5.7. Tools 5.8. Procedures 5.9. Feedback 5.10. Context 5.11. Tasks

  ).
• In this search, the software was instructed to create a citation for each paragraph in which any of the terms appeared. This entry was coded using the subcode shown in Table 1.
• For the analysis, the course guides were selected where there was at least one citation of the codes used, resulting in a total of 5493 guides (

  Table 2. Number of Course teaching guides analysed.

  University	Total Number of Teaching Guides 7810		Selected Number of Teaching Guides 5493
  UC	1803 23%	Initial screening using ATLAS.ti search tool	1422 26%
  UMU	2610 33%		2280 42%
  USC	3397 44%		1791 32%

  ).

2.3. Data Analysis

A deductive analysis was carried out by searching through pre-established categories using theoretical coding (directed coding or deductive coding). This was done by assigning codes or labels to the data according to a pre-existing theory, conceptual framework or hypothesis [45]. This type of coding is based on a set of concepts, categories or variables identified prior to examining the data; that is, a theoretical framework is used to guide the coding process.

This methodology is particularly useful when well-established theories need to be validated or refuted [46]. It helps researchers to focus their analysis on specific and relevant aspects of the data, ensuring consistent and systematic interpretation [47]. By employing a deductive approach, it was possible to identify patterns and relationships that confirmed, extended or challenged the theoretical framework used, providing a solid basis for informed conclusions.

To ensure coherence and analytic rigour in this study’s qualitative coding process, we implemented a multi-step strategy grounded in established methodological guidance. First, we adopted iterative coding, cycling repeatedly between the data and emerging codes to refine interpretations as recommended [48]. Second, the team conducted consensus meetings at key stages to compare coding decisions, resolve discrepancies, and strengthen shared analytic understanding, following recent recommendations for systematic disagreement resolution [49]. During these meetings, extensive code refinement was conducted, adjusting definitions, clarifying inclusion criteria, and reorganizing overlapping codes to enhance conceptual clarity. Finally, we applied researcher triangulation, incorporating multiple analytic perspectives to minimize individual bias and support the credibility of findings, a practice increasingly emphasized in contemporary methodological literature [50]. Together, these procedures produced a transparent and trustworthy coding framework that remained robust even in the absence of full initial intercoder agreement.

The following steps were taken in the analysis of the teaching guides:

• An initial meeting was arranged to establish a theoretical framework for the study by identifying key concepts relevant to the research topic and developing theoretical categories and their respective subcategories. These categories guided the coding.
• Selecting and preparing the data. Data were collected from each of the public websites of the participating universities and organised using the ATLAS.ti software (25 version).
• Applying pre-defined codes. Preliminary coding was carried out using the programme’s search tool by one of the researchers, who is an expert in using the programme and an official trainer for it.
• Reviewing and refining the coding system (consensus meetings). Once the initial selection had been made, a second meeting was held to outline the steps for reviewing the citations generated by the software. Seven researchers manually organised and refined the information into 4 main categories: what is assessed; who is assessed, or for whom assessment is conducted; what assessment is for; and how assessment is conducted. A further total of 57 subcategories can be consulted in the University of Murcia repository DataSet (http://hdl.handle.net/10201/144600, accessed on 6 April 2026) or in Table 1. Once 30% of the review had been completed, a third meeting was arranged to assess the coding work carried out so far.
• Analysing coded data: Once the review was complete, a fourth meeting was held to consider how the coded fragments could be used to identify theoretical concepts, and to reflect on how the patterns observed in the data might confirm, modify or refute the predefined theoretical categories.
• Writing a report.

2.4. Quality Criteria

The trustworthiness principle was followed in order to maintain the credibility and validity of the research conducted [51,52]. This ensured that the results accurately reflected the facts and that research was rigorously performed. To this end, the criteria of credibility, transferability, dependability and confirmability were taken into account. These criteria were used as follows:

Credibility: The data were extracted from the teaching guides in use at the time of data collection. These were publicly available on each of the websites of the universities participating in the study.

Transferability: The characteristics of the data exploration meant that validity was recognised. This exploration was grounded in assessment theory and the framework of the European Higher Education Area (EHEA), the context in which the degrees under study were offered. The recognition of validity thus supports the potential transferability of the findings to other contexts.

Dependability: In this type of research, dependability is established by following an explicit and well-defined protocol which provides transparency and replicability, as well as reinforcing the reliability of the results. Consistency was also ensured in the study because the data analysed were extracted from objective sources and covered the entire study population.

Confirmability: The coding scheme was agreed between the researchers, and data triangulation was conducted across the three universities from which the data had been sourced. Confirmability refers to the attempt to provide information that is as consensual as possible and therefore striving for objectivity and neutrality. It proved especially valuable to specify the frame of reference from which statements were made (researcher’s position); to return the information for ongoing and, at times, collaborative validation (participant verification); and to corroborate the information through the use of multiple techniques and informants (triangulation).

3. Results

3.1. What Aspects of Student Learning Are Most Commonly Identified as the Object of Assessment in the Teaching Guides of Three Spanish Universities?

Of the total number of subcategories that emerged in the analysis, 20 were identified as related to what is assessed, i.e., the object of assessment. Those presented here were the most relevant and predominant in the analysis.

What: 2.3. Ability: basic skills that enable learners to do something or at least learn how to do something. ‘The assessment will focus on the ability to identify and organise the main concepts presented’ (D1198:1). (The references used for the quotations extracted were those generated by the data analysis software. Each reference starts with the letter D followed by a number (indicating the document number) and a colon; this is followed by a second number (indicating the specific quotation within the document)). Reference was made to skills regarded as transversal across the different degree programmes. Certain descriptors were predominant across the three universities. The identified abilities included core skills required for work in higher education, including information analysis, synthesis, presentation and argumentation. There were also anecdotal descriptors that were formulated as skills, which related to the standards set for the performance of activities, e.g., a teaching guide from the UMU referred to ‘planning skills and timely completion of assignments; ‘adaptation skills and flexibility’ (D2495:8).

What: 2.7. Practical work: contextualised application of theoretical contents. ‘Assessment of practical work shall be carried out through monitoring reports, together with questionnaires, problem-solving tasks and case studies’ (D665:4). No differences were found between the three universities; the descriptor with the highest frequency of references was the one related to the practical dimension of certain activities or exercises, which formed part of the assessment. The teaching guides should specify how this aspect should be incorporated in the assessment of the teaching-learning process. These practices recurrently appeared in the teaching guides as a component of the assessment, identifying the assessment instruments or tests that would be used and their percentage of the total mark. Practical work was presented as part of the twofold structure of knowledge. Thus, knowledge was understood as something fragmented, or as one part of a dual concept, which suggests a lack of connection between its components, where practice was seen as running parallel to theoretical content rather than being interconnected with it.

What: 2.9. Attitude: expected behaviours and consensual norms that contribute to creating a climate conducive to learning. ‘The assessment of the acquisition of skills and attitudes shall be carried out on a continuous basis, based on students’ performance in the required tasks’ (D5762:1). In some cases, although the specific content (what) was not clearly defined, a description was provided regarding the nature of the attitude to be assessed: ‘Students should display an academic attitude’ (D3240:2). In other instances, specific details were given as to the exact situation where this attitude was to be assessed, which included a link to the individual characteristics of different degrees: ‘attitude to be exhibited in the laboratory’ (D5293:2).

What: 2.12. Competencies: students’ skills, abilities and knowledge that enable them to perform a task in different contexts. ‘The assessment of the subject encompasses all activities undertaken throughout the semester, considering various aspects related to the acquisition of the competencies cultivated within the subject’. (D5446:2). Many teaching guides (specifically, those at the UCO and the USC) simply listed the competencies to be assessed in each subject as detailed in the course syllabus (indicating, however, the assessment instruments or procedures to be used for this purpose). It was striking to see how many aspects were covered regarding the way in which competencies were to be assessed, whereas nothing was said about what was to be assessed within them.

What: 2.14. Learning: student achievement. ‘Questions may be asked during each session to assess the students’ learning progress in each of the content areas covered’ (D5826:1). It is interesting to note that learning outcomes as outlined by the UC were linked to the acquisition of theoretical content to be assessed by means of a written examination: ‘The assessment of learning outcomes (accounting for 50% of the final mark) is carried out through a written examination designed to verify the acquisition of the relevant content’ (D382:12). At the USC, practical learning outcomes were differentiated and nuanced, although learning outcomes should combine knowledge, understanding and implementation: ‘Practical learning outcomes shall be assessed’ (D5836:3).

What: 2.16. Knowledge: Although the teaching guides generally did not specify the type of knowledge to be assessed, it can be inferred that they primarily referred to conceptual knowledge. This was either because the assessment scheme reduced the notion of knowledge to something purely theoretical—without acknowledging that it might also encompass students’ skills or attitudes—or because of the way in which the assessment was conducted: ‘an objective essay question, a short answer test, a multiple choice test or a piece of assessment involving completing a certain task, a test consisting of a scale of attitudes developed by students to prove the theoretical knowledge acquired’ (D2237:10). Knowledge was understood as an object of the teaching-learning process and a tool for problem solving. While the purpose of this knowledge was to assimilate a series of specific concepts which may be used instrumentally in some universities on a sporadic basis, there was no indication that this would be the nature of the knowledge to be assessed. This mostly conceptual knowledge is almost exclusively assessed in the case of the three institutions. Knowledge was often presented alongside competencies as the object of assessment.

3.2. Integration of Competency Components in Assessment Design and Differences Across Universities, Knowledge Areas, and Course Types

The initial analysis yielded the identified subcategories and showed how they appeared across different classifications. These classifications were based on the documents analysed, the type of course to which the teaching guide pertained and the academic discipline to which the degree programme belonged.

Table 3. Code-document relation table. Prevalent subcategories, including subject type.

	4.1 FS 1209 325	4.2 CS 2888 728	4.3 OS 1255 289	4.4 PW 73 193	4.5 EDW 68 129	Totales
What: 2.12. Competencies 1840	17.78% 26.01%	16.31% 23.86%	21.38% 31.27%	12.21% 17.86%	32.32% 47.27%	100.00% 29.25%
What: 2.14 Learning 701	18.60% 11.16%	15.97% 9.58%	13.21% 7.93%	46.15% 27.68%	6.06% 3.64%	100.00% 12.00%
What: 2.16 Knowledge 1705	24.99% 22.77%	28.49% 25.96%	23.88% 21.76%	16.66% 15.18%	5.99% 5.45%	100.00% 18.22%
What: 2.3. Ability 891	15.77% 12.89%	15.00% 12.26%	14.99% 12.25%	14.20% 11.61%	40.04% 32.73%	100.00% 16.35%
What: 2.7 Practical work 1210	22.54% 16.76%	22.66% 16.85%	24.70% 18.37%	25.21% 18.75%	4.89% 3.64%	100.00% 14,87%
What: 2.9 Attitude 749	22.36% 10.40%	24.71% 11.50%	18.12% 8.43%	19.19% 8.93%	15.63% 7.27%	100.00% 9.31%
Totales	20.00% 100.00%	20.00% 100.00%	20.00% 100.00%	20.00% 100.00%	20.00% 100.00%	100.00% 100.00%

and

Table 4. Code-document relation table. Prevalent subcategories, including areas of knowledge.

	3.1. Engineering and Architecture		3.2. Social Sciences and Law		3.3. Health Sciences		3.4. Sciences		3.5. Arts and Humanities
	Relative % in the Row	Relative % in the Column	Relative % in the Row	Relative % in the Column	Relative % in the Row	Relative % in the Column	Relative % in the Row	Relative % in the Column	Relative % in the Row	Relative % in the Column
What: 2.12. Competency	48.89%	59.80%	18.93%	23.15%	17.61%	21.54%	0.00%	0.00%	14.58%	17.84%
What: 2.14. Learning	20.29%	8.19%	27.97%	11.28%	17.46%	7.05%	0.79%	0.32%	33.48%	13.51%
What: 2.16. Knowledge	14.39%	17.76%	15.89%	19.60%	23.82%	29.38%	24.42%	30.13%	21.48%	26.49%
What: 2.3. Ability	14.45%	9.29%	30.55%	19.65%	16.03%	10.31%	26.41%	16.99%	12.55%	8.07%
What: 2.7. Practical work	0.91%	0.92%	18.57%	18.77%	15.30%	15.46%	44.08%	44.55%	21.14%	21.37%
What: 2.9. Attitude	8.33%	4.05%	15.52%	7.54%	33.48%	16.27%	16.49%	8.01%	26.18%	12.72%

provide the standardised results for the prevalence of each subcategory within the document group to which it belonged. (ATLAS.ti facilitates the standardisation of emerging quotations, making them comparable with one another and preventing any discrepancies that may arise from differences in data volume across document groups. The tables show two percentages, one pertaining to the presence of the category in all groups of documents (row frequency) and another that relates to the distribution of the categories in that group of documents (column frequency)). The distribution of the subcategory in each of the groups is shown in the relative frequency rows, whereas the relative frequency columns indicate the distribution of all categories within that group.

Table 3 illustrates the distribution of the subcategories by type of subject (Foundational subjects (FS); Compulsory (subjects) (CS); Optional (subjects) (OS); Practical work (PW); End-of-Degree Work (EDW)). Several aspects are noteworthy, particularly the prominent presence of the subcategory related to Competencies and skills within the section dedicated to the Final Dissertation. As this was a final project, the guidelines clearly stated that the competencies acquired during the course should be demonstrated, thereby showcasing each student’s various skills. However, they were not considered to be learning instruments in themselves or to provide knowledge. In the other subjects, a notably high percentage of the Learning subcategory was observed in curricular practical work, in contrast to the lower percentages recorded in the remaining subjects, where the Knowledge subcategory was significantly more prominent.

Overall, as can be seen in Figure 1, the Competencies subcategory had a greater presence, with a considerable difference compared to the other subcategories. This importance was most noticeable in the Final Degree Project, along with the Ability subcategory. This makes sense, given the integrative nature of this subject and its aim to use the competencies that students have acquired through the other subjects and/or courses studied. Also important were the data obtained in the optional subjects that offered students a practical specialisation and, therefore, combined competencies, knowledge and practical skills. The Knowledge subcategory was important in the compulsory subjects.

A correspondence can be seen between Figure 1 below and Table 3 above, since subcategories such as Attitude have very little presence, even though they are important components of competencies, as are skills and knowledge.

An analysis of the presence of the subcategories across the different areas of knowledge (Table 4) revealed notable findings and distinctions among them. There was a greater emphasis on what is to be learned in Social Sciences and Law, especially in terms of skills and learning, which was not as strong in the other areas. The difference in the Competency subcategory between engineering and science was also noteworthy. While this subcategory accounted for almost half of the quotations in Engineering, in the sciences it was hardly present at all. Knowledge was relatively evenly distributed across all areas, although with a slight decrease in Engineering and Social Sciences and Law. It is worth noting that this subcategory was the most predominant in three specific areas: Health Sciences, Sciences and Arts and Humanities.

Three main categories can be identified in the diagram below (Figure 2), Practical work, Knowledge and Competency, which stand out from the others. This result is consistent with the findings presented above, with a few exceptions, such as Learning, which had a reduced presence overall.

3.3. Relationships Between the Different Subcategories That Emerged in the Analysis

Having described the different prevalence of the subcategories in the groups of documents used, the content of these categories and how they were related is shown below. The co-occurrences among the selected items were examined, and the results are displayed in

Table 5. Table of co-occurrences between subcategories.

	What: 2.12. Competencies	What: 2.14. Learning	What: 2.16. Knowledge	What: 2.3. Ability	What: 2.7. Practical Work	What: 2.9. Attitude
What: 2.12. Competencies	0.00	0.04	0.05	0.04	0.05	0.02
What: 2.14. Learning	0.04	0.00	0.03	0.04	0.03	0.02
What: 2.16. Knowledge	0.05	0.03	0.00	0.07	0.04	0.26
What: 2.3. Ability	0.04	0.04	0.07	0.00	0.05	0.03
What: 2.7. Practical work	0.05	0.03	0.04	0.05	0.00	0.03
What: 2.9. Attitude	0.02	0.02	0.26	0.03	0.03	0.00

. The values shown represent ATLAS.ti’s c-coefficient, which measures co-occurrence between codes on a scale from 0 to 1: a value of 0 indicates no co-occurrence, while values approaching 1 indicate that two codes consistently appear in the same quotations. Values above 0.15 are considered indicative of a meaningful association between categories.

This table illustrates the existence of varying degrees of association among the categories. The relationship between What/Attitude and Knowledge was particularly prominent. This suggests that it will serve as a central axis of analysis, around which the remaining categories appear to revolve due to the strength of their interconnections. The same can be seen in Figure 3, which shows the relationships mentioned above.

The analysis of these relationships gave rise to the semantic network depicted in Figure 4. It shows how the Competencies, the core of our study, were organised into their theoretical components. However, Ability was part of this structure, but was isolated in relation to the other sub-categories. In contrast, Knowledge and Attitudes emerged as the axes that articulate the content analysed. Within these two subcategories, the data led to classroom teaching practice, as indicated in the subject guides. In turn, this practice was the basis of Learning. Therefore, the teaching guides identified a common thread that led to the objectives in the different degrees, although, in some cases, their actual implementation was not completely aligned with the theory.

4. Discussion and Conclusions

The documents analysed represent statements of intent issued by the academic staff at the various universities, aimed at ensuring compliance with institutional and educational requirements. Competency assessment was the most important category in the three universities participating in this research which directly relates to RQ1, as it reveals which aspects of student learning are most commonly highlighted as the object of assessment in teaching guides. This shows that, when the teaching guides referred to the assessment of learning outcomes, it was the category ‘what is assessed’—what essential questions must be included in the assessment schemes—that was of interest to teachers. However, differing conceptions were found regarding what competency assessment meant and, more specifically, regarding the object of assessment (competencies being part of it), a finding that further illuminates the patterns identified in RQ1.

It was interesting to observe that in universities where competencies were identified as an object of assessment, the focus tended to be on how to evaluate them (i.e., the procedures for gathering information), without addressing what exactly was being evaluated within those competencies. This point is directly relevant to RQ2, as it shows that the constituent elements of competencies (knowledge, know-how, know-how to be, and know-how to be around others) were not consistently or holistically integrated into assessment design. According to these data, it seems that the most important thing was to have clarity (or to make clear) in the didactic plans on how assessment was to be carried out, and what needed to be assessed remained mostly anecdotal [53].

There were also some differences between the universities studied. The assessment of competencies was given a predominant place at the USC when considering what needs to be assessed in terms of student learning. In contrast, at the UMU, when considering what to assess, knowledge, practical work, abilities, attitudes and lastly, competencies, were predominant [54]. These findings respond directly to RQ3, as they indicate differences in assessment focus across universities, and suggest that institutional cultures shape how learning outcomes are prioritised. It is striking that, within a competency-based teaching model, the assessment of competencies was not the first focal point for assessing student learning. It is also clear that competencies themselves included the acquisition of theoretical knowledge; practical ability (cognitive and practical skills); and attitudes, values and behaviours and interaction [38,39,55]. Along these lines, Le Boterf [26] and others [56,57] emphasised competency as a form of combinatory knowledge. However, competency assessment was fragmented into separate elements—knowledge, skills, practical work, attitudes, etc.—which, rather than being understood as an evaluation of a student’s all-round learning, was conceived in a disjointed and differentiated manner. It should not be forgotten, moreover, that the very configuration of Bachelor’s degrees from a multidisciplinary academic perspective requires and demands assessment approaches that transcend individual disciplinary boundaries, favouring models that consider professional and academic competencies.

This calls into question whether the innovative side of higher education [10,58], i.e., competencies, is in fact being assessed [10,59]. Judging by these results, university assessment schemes should be committed to evaluating all-round education [60]. This approach should consider the interdisciplinary nature of the degrees and, therefore, the competencies of university education—an implication that cuts across RQ1 and RQ2. This approach should consider the interdisciplinary nature of the degrees and, therefore, the competencies of university education [61]. It should therefore contemplate that students can collaborate and learn from within different areas of knowledge, which provides them with an overarching, more complex overview of the problems and solutions. This entails a change in the organisational structure of universities. In line with the objective of the project of which this study is a part, it can be argued that a fragmented and department-based institutional organisation may either contribute to or hinder the implementation of competency-based assessment [62,63]. This institutional variation again aligns with the concerns addressed in RQ3, as it highlights how differences between universities may influence assessment priorities and practices.

4.1. Limitations

Although the study implements procedures to strengthen transparency and analytic rigor, several limitations must be acknowledged. First, the process of screening and selecting documents, despite the application of explicit inclusion criteria, may still have restricted the diversity of the materials analyzed, as the variability in the format and completeness of teaching guides can influence which documents are ultimately retained. Second, although multiple strategies were employed to enhance coding consistency—such as iterative coding cycles, consensus meetings, ongoing code refinement, and triangulation among researchers—the absence of formal intercoder agreement metrics remains a methodological constraint. While these qualitative strategies mitigate inconsistency, the lack of a statistical reliability index limits the extent to which the coding process can be externally validated. Finally, the study focuses exclusively on the analysis of teaching guides as documentary sources, without examining how the pedagogical intentions expressed in these documents are enacted in real classroom settings. This restricts the ability to evaluate the alignment between planned and implemented curricula, and limits the extent to which conclusions can be generalized beyond the specific institutional context examined. Despite these limitations, the data provide insight into the elements emphasized in the universities studied and offer a basis for reflecting on the coherence between competency-based teaching models and institutional assessment, while also indicating the need for research that connects documentary analysis with classroom practice and explores these dynamics across a wider range of higher education contexts.

4.2. Implications

This study points to several avenues through which future research could further illuminate the role of teaching guides in ensuring curricular coherence and strengthening pedagogical alignment. By showing how teaching guides articulate learning objectives, expected outcomes, instructional strategies, and assessment criteria, the findings highlight the need to examine how these planned intentions are translated into classroom activity. This suggests the importance of research that investigates the alignment between planned and enacted curricula, offering insight into how teaching guides function not merely as formal documents but as instruments that shape teaching and learning processes. Such work would help clarify the extent to which teaching guides effectively support instructional design, student understanding, and the coherence of learning trajectories.

At the same time, the patterns observed in this study underscore the value of expanding the scope of inquiry beyond a single institutional context. Given the diversity of regulatory environments, curricular models, and pedagogical traditions across the European Higher Education Area, extending analyses to universities in other EHEA countries would enable comparative perspectives on how teaching guides are structured, interpreted, and used. Such cross-national research could identify both shared principles and context-specific variations, contributing to a more comprehensive understanding of teaching guides as tools for curriculum development and quality enhancement. Together, these implications point to the need for future studies that both triangulate document analysis with real classroom practice and broaden the geographical and institutional dimensions of analysis.