A longitudinal perspective on student engagement: A follow-up study of students at Chilean Universities ^*1

Abstract

This article presents the results of a longitudinal study on student engagement among Chilean university students, drawing on data from the National Survey of Student Engagement (ENCE). The study follows a cohort of undergraduate students at two points in time: upon entry to university in 2019 and at the end of their fourth year in 2022. Three dimensions of student engagement relevant to the formative experience and academic outcomes were analyzed: Higher-Order Learning (AOS), Learning Strategies (EA), and Institutional Support (AI). The findings show no significant changes in Higher-Order Learning between 2019 and 2022. However, by the fourth year, students reported less frequent use of several effective learning strategies. In the Institutional Support dimension, overall perceptions remained relatively stable, although students reported a significant decline in institutional encouragement to use learning support services. As one of the first longitudinal studies of student engagement in Chile, this research provides empirical evidence on how university students experience their educational trajectories and identifies trends, impacts, and transformations in that experience. The conclusions may inform institutional policies and practices aimed at sustaining student engagement and improving learning in higher education.

Keywords:
Student engagement - Higher education - Chilean universities - Longitudinal study

Resumen

Este artículo presenta los resultados de un estudio sobre compromiso estudiantil en estudiantes universitarios chilenos, utilizando un diseño longitudinal, basado en los datos de la Encuesta Nacional de Compromiso Estudiantil (ENCE) para analizar una cohorte de estudiantes de pregrado en dos momentos: al ingresar a la universidad en el año 2019 y cuando terminaban su cuarto año en 2022. Se analizaron tres dimensiones del compromiso estudiantil, relevantes para la experiencia formativa y el logro de resultados académicos: Aprendizaje de Orden Superior (AOS), Estrategias de Aprendizaje (EA) y Apoyo Institucional (AI), con el objetivo de comprender cómo evoluciona el compromiso de los estudiantes a lo largo de su formación universitaria. Los resultados mostraron que no hubo cambios significativos en la dimensión Aprendizaje de Orden Superior entre 2019 y 2022; no obstante, en el cuarto año se observó una disminución en el uso de ciertas estrategias efectivas de aprendizaje. En la dimensión Apoyo Institucional, la percepción general se mantuvo relativamente estable, aunque se registró una disminución significativa en la promoción del uso de servicios de apoyo al aprendizaje. El estudio es pionero en Chile en el análisis del compromiso estudiantil con un diseño longitudinal. Sus resultados aportan evidencia empírica relevante sobre cómo los estudiantes universitarios experimentan su trayectoria formativa, permitiendo identificar tendencias, impactos y transformaciones en su vivencia universitaria. Las conclusiones pueden orientar el diseño de políticas y prácticas institucionales que promuevan un compromiso estudiantil sostenido y contribuyan a mejorar la experiencia de aprendizaje en la educación superior.

Palabras claves:
Compromiso estudiantil - Educación superior - Universidades chilenas - Estudio longitudinal

Introduction

Concern about the quality of higher education, both in Chile and worldwide, has generated growing interest in understanding the factors that shape students’ experiences and their impact on learning outcomes. In this context, student engagement-understood as students’ active disposition to become involved in their educational process, as well as institutional efforts to facilitate and sustain such involvement-emerges as a key analytical category for the study of teaching and learning in university contexts (Kuh et al., 2014; Trowler, 2010; Trolian, 2024).

Numerous studies have shown that high levels of engagement are positively correlated with indicators of academic success, retention, and holistic development throughout the university trajectory. Most of this research, however, is based on cross-sectional designs, with limited longitudinal studies that make it possible to observe the evolution of engagement over time and at different points in the educational cycle. Thus, analyzing how student engagement evolves throughout higher education helps advance the understanding of a phenomenon that is fundamentally dynamic and refers to a sequence of cumulative and contextual experiences in which engagement and sense of belonging develop over the course of students’ education (Thomas, 2012; Smith; Tinto, 2024).

In the Chilean context, although there is research on the university experience and on the use of instruments inspired by international models, such as the National Survey of Student Engagement (NSSE), systematic assessments using follow-up designs that capture the dynamic nature of the relationship between students and institutions remain scarce. In this scenario, the National Survey of Student Engagement (ENCE) represents a pioneering effort in the country-and in the region-to generate empirical evidence on the student experience in universities.

This article presents the results of one of the first longitudinal panel studies in Chile focused on student engagement. It follows a cohort of undergraduate students at two key points in their educational trajectory: in 2019, when they had recently entered university and were in the first year of their programs, and in 2022, when they were in their fourth year and approaching graduation. The analysis examines three core dimensions of engagement: Higher-Order Learning (AOS), Learning Strategies (EA), and Institutional Support (AI). These dimensions allow the study to address both students’ cognitive and learning practices and the institutional conditions that support their development. The cohort also experienced the pandemic and lockdown period between 2020 and 2021, a context that may have substantially shaped the dimensions analyzed and that makes the longitudinal comparison particularly relevant (González et al., 2020; Kuh; O’Donnell, 2013).

Overall, the study contributes to the international literature on student engagement by showing how selected dimensions of the university experience evolve over time in a Chilean context. It also responds to a practical need within the Chilean university system: the availability of systematic, valid, and sustained evidence to inform institutional management, student support mechanisms, and quality assurance decisions.

Theoretical framework

Student engagement and the student experience in higher education refer to the disposition to engage with academic work and achieve learning outcomes through interaction with the conditions and opportunities provided by institutions. These are central variables for understanding and improving educational processes at the university level (Kuh et al., 2014), particularly because they can be influenced through institutional action.

This study is framed within the perspective of Student Learning Research (Trowler, 2010; Trolian, 2024), which emphasizes the need to document evidence on students’ educational experience and their level of engagement as key elements for achieving learning outcomes. Learning develops in multiple ways, both inside and outside the classroom, through a variety of academic and non-academic activities. In this context, student engagement can make a significant contribution to better academic performance and achievement (Kuh, 2009; Trowler, 2010; Zapata et al., 2018; Kinzie; Franklin, 2020; Trolian, 2024).

The student experience, in turn, has a relevant contextual component (Coates, 2007), and its behavioral, emotional, and cognitive dimensions tend to vary in response to the environment (Fredricks et al., 2004). Consequently, engagement must be understood as a dynamic and multidimensional phenomenon that is sensitive to the changing conditions of the educational environment.

Along these lines, the National Survey of Student Engagement (ENCE), which has been administered in Chile systematically and on a large scale since 2018 (Zapata et al., 2018; Del Valle; Cumsille, 2019; Zapata et al., 2023), represents a significant progress for the analysis of engagement in the national university context (Leihy, 2022). This instrument measures student engagement through seven dimensions of the experience, covering diverse aspects associated with how students approach their learning, including academic challenge, learning with peers, experiences with faculty, and the university environment, among the most important. Each dimension is constructed from between four and eight items -specific questions-assessed according to the level of frequency with which students report having carried out certain practices during the university year.

The assumption underlying this perspective is that learning requires a strong investment of time and effort on the part of students, while higher education institutions must develop consistent activities and provide appropriate conditions for the achievement of effective learning (Kuh, 2009; Trowler, 2010; Zapata et al., 2018; Trolian, 2024). Thus, the focus is on better understanding how students engage with their learning and what institutions can do to improve their policies and practices in ways that foster learning achievement. This is not a matter of individual attitudes alone, but rather a collective construction that considers both the predispositions associated with student diversity and the social and institutional context (Zepke; Leach, 2010; Case, 2008). Within the ENCE framework, this study focuses on three specific dimensions of student engagement that have shown relevant links with academic performance throughout the university trajectory: Higher-Order Learning (AOS), Learning Strategies (EA), and Institutional Support (AI) (Chen et al., 2009; Fiorini et al., 2014; Parnes et al., 2020).

The Higher-Order Learning (AOS) dimension captures the extent to which courses emphasize complex cognitive tasks, such as the acquisition of new knowledge, the practical application of theories and methods, analysis, the formulation of judgments, and the synthesis of ideas (González et al., 2017). It includes the analysis of information sources and the use and systematization of quantitative information to address problems. Indeed, intellectual challenge and creative work are central to student learning and university quality. Universities promote high levels of student performance by asking students to engage in complex cognitive tasks that require more than the memorization of facts; therefore, this is a key dimension from the perspective of the student experience.

For its part, the Learning Strategies (EA) dimension addresses how university students improve their learning and persistence through active participation and analysis of course material, rather than approaching learning through passive assimilation. Learning strategies are essential as effective means for students to achieve learning objectives, such as identifying key information, reviewing notes, summarizing course material, and participating in class (Dumford et al., 2016). This dimension also considers class participation and group work. Understanding the prevalence of effective learning strategies helps universities target interventions to promote student learning and success.

Institutional Support (AI), in turn, refers to the institution’s commitment to student success, expressed through services and activities that support students’ learning and development-academic and socioemotional guidance, socioeconomic support, library services, among others-which students may use to varying degrees depending on a range of variables (Valenzuela et al., 2021a; Valenzuela et al., 2021b; Parnes et al., 2020). These supports are fundamental for persistence and academic success among a substantial proportion of students, especially in a context of higher education massification such as Chile (Engstrom; Tinto, 2008). Institutional support fosters higher levels of performance and satisfaction among students through a variety of activities and domains that contribute to cognitive, social, and physical development.

Despite growing interest in student engagement, much of the empirical literature remains based on cross-sectional studies. Although such studies have been fundamental for identifying associations between practices and engagement levels, they offer only a static view of phenomena that are dynamic and contextually mediated (Kahu, 2013; Case, 2008). They therefore provide limited insight into stability, change, transitions, or the accumulation of experiences that shape students’ trajectories within evolving institutional contexts. Longitudinal designs, such as the one adopted in this study, are therefore especially useful for understanding variations in engagement over time and the interaction between individual dispositions and institutional conditions at different stages of the educational cycle (Astin, 1993; Briggs et al., 2012; Smith; Tinto, 2024).

Method

This study uses a quantitative, empirical, descriptive-comparative approach based on a longitudinal panel design (Schober; Vetter, 2018). It analyzes the evolution of student engagement in Chilean universities by focusing on three key dimensions: Higher-Order Learning (AOS), Learning Strategies (EA), and Institutional Support (AI). These dimensions, which are central to academic performance, are measured through the National Survey of Student Engagement (ENCE), an instrument validated for the Chilean population (Zapata et al., 2018; Leihy, 2022).

The longitudinal design makes it possible to examine changes in student engagement over time, providing empirical evidence on the impact of institutional conditions and academic practices on students’ educational trajectories.

Participants

The sample was non-probabilistic and comprised 384 undergraduate students enrolled in programs lasting at least four years at nine universities belonging to the Council of Rectors of Chilean Universities (CRUCh). Participants were purposively selected in order to observe trends within institutions that are broadly representative of the Chilean university system.

The sample distribution by type of institution was as follows: 149 students came from private regional universities and 235 from state universities. Within the latter group, 110 students belonged to state universities in the Metropolitan Region, while 125 studied at state universities in other regions of the country. In terms of gender, the sample included 102 students assigned males at birth and 282 assigned females at birth. Regarding age, in 2019 the mean was 20.1 years (SD = 2.92), with a range from 17 to 38 years. In 2022, the mean age increased to 22.8 years (SD = 2.93), with a range from 20 to 40 years.

Table 1
Frequency by Type of University

Type of University	Frequency	Percentage
Private Universities	149	38.8%
State Universities	235	61.2%
Metropolitan State Universities	110	46.8%	(of state universities)
Regional State Universities	125	53.2%	(of state universities)
Total	384	100%

• Note: The “State Universities” category is broken down into metropolitan and regional universities, showing the relative percentage within the total number of state universities. The total number of participants was 384.
• Source: National Survey of Student Engagement Project, CRUCh.

Procedure

Participants were assessed at two points in their academic trajectory: during their first year of undergraduate studies (second semester), in 2019, and subsequently during their fourth year (eighth semester), in 2022. On both occasions, they were invited to participate voluntarily by their respective universities via email and completed the survey in digital format. To safeguard participants’ anonymity and confidentiality, no direct personal data or sequential code that would allow individual students to be identified were used. Instead, a coding system was employed based on participants’ background information and prior records: the code of the secondary school from which they graduated (RBD), the weighted score on the University Selection Test (PSU) with which they entered higher education, the secondary-school grades score (NEM) assigned according to their high-school grade point average, and the higher education institution in which they were enrolled. This procedure enabled longitudinal follow-up of participants while maintaining direct anonymization of the data. Since no cases were recorded in which the simultaneous combination of these background characteristics coincided in more than one subject, this strategy made it possible to generate a unique indirect code for each participant.

Instrument

ENCE measures student engagement through seven dimensions of student experience, including academic challenge, learning with peers, experiences with faculty, and institutional support. Originally designed and validated in 2017, the questionnaire includes 35 composite variables and 48 items related to student experience. It also incorporates 42 personal, socioeconomic, and academic characterization variables obtained through cross-referencing with other institutional databases. In addition, the questionnaire collects students’ perceptions of practices considered “high impact” in the specialized literature, given their contribution to improve engagement, as also asks about their perceptions of time use, expectations, and achievements (Zapata et al., 2018, 2023).

Measures

For this study, only three specific ENCE dimensions of student engagement were analyzed: Higher-Order Learning (AOS), Learning Strategies (EA), and Institutional Support (AI). For each of them, reliability analyses were conducted for both the 2019 and 2022 measures, using McDonald’s omega and Cronbach’s alpha.

Higher-Order Learning (AOS)

The Higher-Order Learning (AOS) dimension in ENCE is composed of five items that begin with the statement: “During this year at the UNIVERSITY, how much has the following been emphasized in your subjects, courses, or classes?” The items include statements such as “Formulating new ideas or perspectives based on information from diverse sources.” Students respond using a 4-point Likert scale, where 1 represents “Very little” and 4 represents “Very much.”

Learning Strategies (EA)

The Learning Strategies (EA) dimension consists of eight items that begin with the statement: “During this year at the UNIVERSITY, how often have you done the following?” The items include questions such as “Reviewed your notes after class,” and students respond on a 4-point Likert scale, where 1 is “Never” and 4 is “Very often.”

Institutional Support (AI)

The Institutional Support (AI) dimension is composed of seven items that begin with the statement: “To what extent does the UNIVERSITY or PROGRAM do the following?” The items include questions such as “Provide support so that students can achieve academic success,” and students respond on a 4-point Likert scale, where 1 corresponds to “Very little” and 4 to “Very much”

Data analysis

Repeated-measures analyses of variance were conducted separately for each scale: Higher-Order Learning (AOS), Learning Strategies (EA), and Institutional Support (AI). The analyses compared participants’ responses to each scale item at two different time points, 2019 and 2022. Mauchly’s W test was used to assess sphericity assumption. When this assumption was violated, degrees of freedom were adjusted using the Greenhouse-Geisser correction when the sphericity coefficient (ε) was equal to or below 0.75 and the Huynh-Feldt correction when the violation was mild (ε > 0.75). Partial eta squared (η²p) was used to estimate effect size. Finally, Bonferroni-adjusted post hoc comparisons were conducted to identify item-level differences between 2019 and 2022 within each scale.

Results

As shown in Table 2, the reliability of the ENCE questionnaire scales-Higher-Order Learning (AOS), Learning Strategies (EA), and Institutional Support (AI)-was assessed using McDonald’s ω and Cronbach’s α coefficients. Overall, the AOS and AI scales showed adequate levels of internal consistency in both years (Dunn et al., 2014). However, the Learning Strategies scale in 2019 showed questionable reliability coefficients (α = 0.647; ω = 0.642), indicating lower measurement precision for Learning Strategies during that period. Taken together, the results suggest that most of the measures used here present acceptable levels of reliability for assessing student engagement.

Table 2
Reliability statistics of the measures by year

Scale	No. of valid cases	McDonald’s ω	Cronbach’s α
Higher-Order Learning 2019	367	0.790	0.780
Higher-Order Learning 2022	358	0.837	0.831
Learning Strategies 2019	358	0.642	0.647
Learning Strategies 2022	355	0.744	0.746
Institutional Support 2019	355	0.873	0.872
Institutional Support 2022	384	0.933	0.933

• Note. McDonald’s ω and Cronbach’s α reliability coefficients are presented for each scale assessed in 2019 and 2022.
• Source: National Survey of Student Engagement Project, CRUCh.

In the repeated-measures ANOVA for the AOS scale, significant within-subjects differences were observed across the AOS items (F_{(3.64, 2628.18)} = 28.27, p < 0.001, η²p = 0.038), with degrees of freedom adjusted using the Huynh-Feldt correction (ε = 0.909) because the sphericity assumption was violated. The AOS × Year interaction was not significant (F_{(3.64, 2628.18)} = 1.08, p = 0.364, η²p = 0.001), suggesting that the pattern of emphasis on higher-order cognitive tasks remained stable between 2019 and 2022. In addition, no significant year effect was observed (F_{(1, 723)} = 0.001, p = 0.973, η²p = 0), indicating that average AOS scores did not differ significantly between 2019 and 2022. Post hoc comparisons (see Table 3) with Bonferroni correction showed no significant differences between 2019 and 2022 in any scale item: AOS1 (t₍₇₂₃₎ = 0.127; p = 1.00), AOS2 (t₍₇₂₃₎ = -0.715; p = 1.00), AOS3 (t₍₇₂₃₎ = 1.028; p = 1.00), AOS4 (t₍₇₂₃₎ = 0.254; p = 1.00), and AOS5 (t₍₇₂₃₎ = -0.789; p = 1.00). These results suggest that, although the scale remained stable over time, students did not report significant development in the emphasis placed on complex cognitive tasks.

Table 3
Post Hoc Comparisons for Higher-Order Learning by Year

Comparison					Mean Difference	SE	df	t	p Bonferroni
Item	Higher-Order Learning	Year		Year
AOS1	Acquiring new knowledge	2019	-	2022	0.006	0.048	723	0.127	1.000
AOS2	Applying methods to practical problems	2019	-	2022	-0.038	0.054	723	-0.715	1.000
AOS3	Analyzing ideas in depth	2019	-	2022	0.056	0.055	723	1.028	1.000
AOS4	Evaluating viewpoints and sources	2019	-	2022	0.014	0.056	723	0.254	1.000
AOS5	Formulating new ideas	2019	-	2022	-0.045	0.057	723	-0.789	1.000

• Note: Mean differences, standard errors (SE), degrees of freedom (df), t statistic, and adjusted significance values are presented for each item of the scale. No comparison was statistically significant after Bonferroni correction.
• Source: National Survey of Student Engagement Project, CRUCh.

Figure 1
Estimated marginal means: Comparison of Higher-Order Learning among first-year (2019) and fourth-year (2022) university students

The repeated-measures ANOVA for the EA scale showed significant differences across the Learning Strategies items (F_{(6.33, 4503.67)} = 40.7, p < 0.001, η²p = 0.054), with degrees of freedom adjusted using the Huynh-Feldt correction (ε = 0.905). In addition, a significant Learning Strategies × Year interaction was observed (F_{(6.33, 4503.67)} = 18.8, p < 0.001, η²p = 0.026), indicating that the frequency with which students reported using these strategies changed over time. A significant year effect was also found (F_{(1, 711)} = 19.2, p < 0.001, η²p = 0.026), suggesting that mean EA scale scores differed significantly between 2019 and 2022. Post hoc comparisons for each EA item (see Table 4) indicated that students in their first year (2019) reported using several strategies more frequently than they did in their fourth year (2022): identifying key information from course readings (EA1; t₍₇₁₁₎ = 3.820; p < 0.05), reviewing notes after class (EA2; t₍₇₁₁₎ = 7.483; p < 0.001), summarizing what was learned in class or course content (EA3; t₍₇₁₁₎ = 3.961; p < 0.05), actively participating in class by asking questions or contributing to course discussions (EA6; t₍₇₁₁₎ = 4.295; p < 0.01), attending teaching-assistant sessions or tutorials or asking a professor for help to better understand course content (EA7; t₍₇₁₁₎ = 4.295; p < 0.01), and studying in groups outside class time (EA8; t₍₇₁₁₎ = 3.711; p < 0.01). These comparisons suggest a reduction in the use of several effective learning strategies as students progressed through their studies. However, reviewing supplementary course material (EA5) was reported more frequently in the fourth year than in the first year (t(711) = -4.002; p < 0.01). By contrast, no significant difference was observed in preparing drafts of an assignment or paper before submission (EA4) between first- and fourth-year students (t₍₇₁₁₎ = -2.800; p = 0.630).

Table 4
Post Hoc Comparisons for Learning Strategies by Year

Comparison					Mean Difference	SE	df	t	p Bonferroni
Item	Learning Strategies	Year		Year
EA1	Course readings	2019	-	2022	0.296	0.078	711	3.820	0.017
EA2	Reviewing notes	2019	-	2022	0.474	0.063	711	7.483	<.001
EA3	Summarizing what was learned	2019	-	2022	0.318	0.080	711	3.961	0.010
EA4	Preparing drafts	2019	-	2022	-0.197	0.070	711	-2.800	0.630
EA5	Reviewing supplementary material	2019	-	2022	-0.273	0.068	711	-4.002	0.008
EA6	Participating actively	2019	-	2022	0.254	0.059	711	4.295	0.002
EA7	Attending teaching-assistant sessions	2019	-	2022	0.286	0.070	711	4.118	0.005
EA8	Studying in groups	2019	-	2022	0.242	0.065	711	3.711	0.027

• Note. Mean differences, standard errors (SE), degrees of freedom (df), t statistics, and significance values adjusted using the Bonferroni correction are reported.
• Source: National Survey of Student Engagement Project, CRUCh.

Figure 2
Estimated marginal means: Comparison of Learning Strategies among first-year (2019) and fourth-year (2022) university students.

The repeated-measures ANOVA for the Institutional Support (AI) scale showed significant differences across the AI items (F_{(5.52, 3896.39)} = 103.11, p < 0.001, _η²p = 0.127), with degrees of freedom adjusted using the Huynh-Feldt correction (ε = 0.920). In addition, a significant AI × Year interaction was observed (F_{(5.52, 1960)} = 4.41, p < 0.001, η²p = 0.006), indicating that changes in students’ perceptions of institutional support varied across items over time. A significant year effect was also identified (F_{(1, 706)} = 17.1, p < 0.001, η²p = 0.024), suggesting an overall change in mean AI scores between 2019 and 2022.

Post hoc tests with Bonferroni correction indicated that students in their first year reported significantly greater encouragement to use learning support services, such as tutoring and mentoring, than students in their fourth year (AI2; t(706) = 6.837, p < .001). For the remaining aspects of institutional support, no statistically significant differences were found between the two academic years, as shown in Table 5. This suggests that, except for encouragement to use learning support services, students’ perceptions of institutional academic support remained stable between the first and fourth years of university education.

Table 5
Post Hoc Comparisons for Institutional Support by Year

Comparison					Mean Difference	SE	df	t	p Bonferroni
Item	Institutional Support	Year		Year
AI1	Support for academic success	2019	-	2022	0.179	0.057	706	3.127	0.167
AI2	Encouraging the use of support services	2019	-	2022	0.428	0.063	706	6.837	<.001
AI3	Fostering interaction among students	2019	-	2022	0.203	0.069	706	2.966	0.284
AI4	Opportunities to socialize within the community	2019	-	2022	0.131	0.068	706	1.919	1.000
AI5	Support for overall well-being	2019	-	2022	0.202	0.068	706	2.989	0.263
AI6	Help with non-academic responsibilities	2019	-	2022	0.149	0.070	706	2.142	1.000
AI7	Encouraging attendance at extracurricular activities	2019	-	2022	0.158	0.074	706	2.138	1.000

• Note. Mean differences, standard errors (SE), degrees of freedom (df), t statistics, and significance values adjusted using the Bonferroni correction are reported.
• Source: National Survey of Student Engagement Project, CRUCh.

Note: The figure shows the average scores reported by first-year students (2019) and fourth-year students (2022) on seven items of the Institutional Support (AI) dimension, assessed on a scale from 1 (Very little) to 4 (Very much). The error bars represent 95% confidence intervals. Mean scores were: AI1. Support for academic success: 2.90 (first year), 2.72 (fourth year); AI2. Encouraging the use of support services: 3.03 (first year), 2.61 (fourth year); AI3. Fostering interaction among students: 2.65 (first year), 2.45 (fourth year); AI4. Opportunities to socialize within the community: 2.44 (first year), 2.32 (fourth year); AI5. Support for overall well-being: 2.77 (first year), 2.56 (fourth year); AI6. Help with non-academic responsibilities: 2.21 (first year), 2.06 (fourth year); AI7. Encouraging attendance at extracurricular activities: 2.69 (first year), 2.54 (fourth year).

Figure 3
Estimated marginal means: Comparison of students’ perceptions of Institutional Support among first-year (2019) and fourth-year (2022) university students

Discussion

This longitudinal study contributes to the analysis of student engagement in Chilean higher education by providing empirical evidence on the evolution of three key dimensions of the university experience: Higher-Order Learning (AOS), Learning Strategies (EA), and Institutional Support (AI). Drawing on data from the National Survey of Student Engagement (ENCE), the study advances understanding of how students learn in the Chilean university context, a complex but essential task for the sustained improvement of higher education quality (Zapata et al., 2023; Trowler, 2010; Trolian, 2024).

First, the results confirmed the stability and reliability of the scales used to measure the dimensions under study, thereby providing methodological robustness to the findings obtained. In particular, an increase was observed in McDonald’s omega and Cronbach’s alpha coefficients across all scales between 2019 and 2022, consolidating ENCE as a valid tool for the longitudinal monitoring of the student experience in the Chilean context. Notwithstanding the above, the results suggest that further adjustments may be developed, especially in the Learning Strategies (EA) dimension.

Regarding the Higher-Order Learning (AOS) dimension, no significant changes were observed in the specific items of this scale in the post hoc comparisons, suggesting relative stability in pedagogical practices that require students to undertake complex cognitive tasks. This stability may have multiple interpretations. On the one hand, it may reflect an institutional effort to maintain pedagogical standards focused on complex cognitive tasks, even during the critical period of the pandemic. This is consistent with an institutional commitment to safeguarding academic quality, in line with González et al. (2020). On the other hand, the absence of variation could also reflect a lack of pedagogical innovation or the persistence of traditional methodologies that are not well adapted to hybrid or virtual contexts, thereby limiting the implementation of more flexible, student-centered approaches.

Although no statistically significant changes were observed in this dimension, descriptive results suggest somewhat greater fourth-year emphasis on higher-order cognitive tasks involving application and creation, a pattern that is consistent with expectations near the end of undergraduate study. This trend should be interpreted cautiously, however, given the absence of statistically significant item-level differences.

Regarding Learning Strategies, significant differences were observed between the two years, especially in items related to active study practices such as summarizing content, reviewing notes, and participating in class. This decline may reflect the effects of the prolonged period of remote teaching, which reduced opportunities for meaningful interaction and active participation-central conditions for the development of effective metacognitive strategies (Dumford et al., 2016; Gherghel et al., 2023).

Likewise, this decline could reflect emotional and cognitive fatigue among students due to prolonged overexposure to digital environments and the reduction of in-person collaborative spaces. In this sense, the results constitute an alert for universities and a challenge to create conditions that encourage students’ active role in their own learning processes, reinforcing active and sustainable study habits.

Regarding Institutional Support (AI), students’ perceptions varied by the fourth year, although the significant change was concentrated in institutional encouragement to use learning support services. These findings are consistent with previous studies that emphasize the importance of institutional conditions for academic success (Engstrom; Tinto, 2008). In particular, the post hoc analysis showed a significant decrease in perceived encouragement to use learning support services (AI2), a key factor for university retention and competency development (Parnes et al., 2020).

The AI indicators, in general, remained stable, as no significant variations were observed in general support for academic success (AI1), student well-being (AI5), or help with non-academic responsibilities (AI6). This shows that institutional efforts may have been maintained over time and that universities continued their support strategies throughout students’ educational trajectories, reinforcing Valenzuela et al. (2021a) regarding the importance of academic support mechanisms for student persistence.

On the other hand, it should be noted that the decline in some indicators, such as perceptions of opportunities for socialization within the community (AI4) and attendance at extracurricular activities (AI7), could be associated with changes in post-pandemic university culture, considering that student interaction spaces have, to some extent, been transformed by virtuality and the diversification of learning formats (Chowdhury; Halder, 2019). These findings reinforce the importance of considering the socioeducational context in the analysis of student engagement and in the design of institutional support policies and strategies.

Although the overall perception of institutional support remained stable between the first and fourth years of study, the observed decrease in the promotion of support services reveals a gap in the consolidation of effective support strategies. This situation represents an opportunity for universities to review and strengthen their support policies, taking into account students’ new realities and needs.

These findings show the need to design strategies aimed at reactivating student engagement, not only from the academic dimension but also through the strengthening of the university’s social fabric. The pandemic has left marks on students’ educational experience, and institutions must recognize and address its effects comprehensively, from a systemic perspective.

Conclusions

This longitudinal study contributes to the analysis of the student experience in Chilean higher education by providing empirical evidence on how selected dimensions of student engagement evolve over time. The analysis of Higher-Order Learning, Learning Strategies, and Institutional Support identified patterns of both stability and change, offering information that may support decision-making in university management and student support.

The results reveal differentiated patterns in the evolution of student engagement. Higher-Order Learning (AOS) remained stable, whereas Learning Strategies (EA) and Institutional Support (AI) showed significant changes. These findings suggest that, although universities maintained academic standards related to advanced cognitive tasks (González et al., 2017), students experienced changes in their study practices and in their perceptions of institutional support, particularly toward the end of their degree programs.

To improve academic performance and student success, Chilean universities should deepen their understanding of student practices, particularly in the final years of study. Interventions designed to strengthen effective learning strategies, together with reinforced institutional support, may improve students’ university trajectories. In addition, programs that promote social interaction and participation in learning communities could help address the decline in students’ perceptions of opportunities for socialization and enrich the student experience (Parnes et al., 2020; Valenzuela et al., 2021a).

The use of longitudinal data, such as those provided by this study, emerges as an essential tool for informed decision-making in university management. These data can contribute to the design of support policies and strategies that are more relevant and better adapted to students’ changing needs, facilitating a deeper and more dynamic understanding of the student experience. From this perspective, the quality of educational processes can be strengthened, while indicators of academic success, retention, and holistic development within the Chilean university system can be improved.

In this context, the National Survey of Student Engagement (ENCE) is established as a key tool for monitoring university trajectories, providing information that can support the design of institutional policies and strategies aimed at promoting student support and academic success in Chilean universities (Zapata et al., 2023).

Measuring student engagement is not a mechanical exercise; rather, it requires analytical and methodological adjustments, with continuous attention to the adequacy of the instrument in relation to the particularities of the context, institutions, and student populations under study (Leihy, 2022). In this regard, although women currently account for 53% of university enrollment in Chile and show higher rates of course approval and retention (Chile, 2025), women represented 73% of the sample in the present study, which should be considered when interpreting the results. Future research should also incorporate direct academic performance indicators, such as grades or course or credit approval rates. Although this study examines the evolution of engagement indicators that the literature links to academic achievement-such as Higher-Order Learning and Learning Strategies-it did not analyze their relationship with direct performance indicators. This relationship remains a relevant avenue for future longitudinal research.

Acknowledgements:

The authors acknowledge the funding provided by the Convocatoria de Apoyos Técnicos para Laboratorios y Grupos de Investigación UPLA, 2024, the Proyecto Ines Género (INGE 220004, A-005), and the sponsorship of the Proyecto Encuesta Nacional de Compromiso Estudiantil, CRUCh.

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*

English version by Carolina Larraín. The authors take full responsibility for the translation of the text, including title of books/articles and the quotations originally published in Spanish.

¹ Data availability:

The full dataset supporting the results of this study has been published in the article itself. The data were obtained under research ethics protocols approved by a certified committee. Further information on the Encuesta Nacional de Compromiso Estudiantil, ENCE, is available here: https://consejoderectores.cl/pregrado-y-sellos-cruch/acerca-de-ence/

Editor:

Prof. Dr. Hugo Heredia Ponce

Publication Dates

• Publication in this collection
  02 Nov 2026
• Date of issue
  2026

History

• Received
  22 Nov 2025
• Reviewed
  24 Feb 2026
• Accepted
  13 Apr 2026