Understanding First-Year Engineering Students' Learning Expectations: Insights for an Entry-Level Mechanics Course

Research Paper Recommended citation: Heylen, M., Van Petegem, W., & Denis, K. (2025). Understanding First-Year Engineering Students’ Learning Expectations: Insights for an Entry-Level Mechanics Course. In Kangaslampi, R., Langie, G., Järvinen, H.-M., & Nagy, B. (Eds.), SEFI 53rd Annual Conference. European Society for Engineering Education (SEFI), Tampere, Finland. DOI: 10.5281/zenodo.17631861. This Conference Paper is brought to you for open access by the 53rd Annual Conference of the European Society for Engineering Education (SEFI) at Tampere University in Tampere, Finland. This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License. Understanding first-year engineering students’ learning expectations: insights for an entry-level mechanics course Maarten Heylen 1 Faculty of Engineering Technology, KU Leuven, Leuven, Belgium ORCID: 0000-0001-5374-1193 Wim Van Petegem Faculty of Engineering Technology, KU Leuven, Leuven, Belgium ORCID: 0000-0002-4553-4407 Kathleen Denis Faculty of Engineering Technology, KU Leuven, Leuven, Belgium ORCID: 0000-0002-6492-9607 Conference Key Areas: Teaching mathematics and physics in engineering education; Improving higher engineering education through researching engineering education Keywords: Student expectations, Student learning, Mechanics, Assessment ABSTRACT First year engineering students bring their own approaches to studying and notions of teaching methods to university. These approaches and notions give them expectations on how to study for courses at university, influencing their quality of learning due to potential misalignment with the teachers’ expectations. In this study, the expectations of students regarding the learning objectives, useful learning activities, type of exam questions and effort required for an entry-level mechanics course, in an engineering program, are investigated. The findings indicate that the learning objectives the students expect to be important align with the learning activities they find useful and the type of exam questions they expect. All three of them focus on applying knowledge to solve problems. However, the results show diverse expectations at the start of the semester concerning learning objectives and learning activities and diverse expectations regarding the type of assessment halfway through the semester. This opens opportunities for better and earlier alignment. 1 Corresponding Author M. Heylen [email protected] 1 INTRODUCTION First-year students arrive at university with preconceived notions about teaching methods and their own approaches to coursework. However, in an environment where stronger learner independence is expected from students (Cameron & Rideout, 2022), these expectations can lead to study behavior or habits that are not aligned with the expectations of the teachers (Elen, 2020; Goodyear et al., 2021). Many factors associated with student success in engineering and science programs have already been investigated (Pinxten et al., 2019; Van Soom & Donche, 2014). Among these factors are prior achievement, teacher judgments, self-efficacy beliefs, self-regulatory skills, and motivation, with prior achievement being the best predictor. However, the quality of learning at university is principally influenced by the students’ approaches to learning and studying as well as their perceptions of the teachinglearning environment (Entwistle & Peterson, 2004). Expectations of students can be an expression of their approaches and influence their perceptions. On top of that, expectations influence how students behave. They make students focus on information that is either consistent or very inconsistent with their expectations, students might behave such that their expectations become reality and their expectations might bias actual experiences (Könings et al., 2008). Additionally, expectations influence the value students attribute to certain tasks and subsequently the motivation the students have to undertake those tasks (Eccles & Wigfield, 2020). The literature on students' expectations in higher education is broad, yet it mainly focuses on general aspects of university life (Brinkworth et al., 2009; Crisp et al., 2009; Surgenor, 2013). This leaves a gap in comprehending how students expect to study for a course and the level of understanding they expect they need to reach. This work aims to discover the expectations of students in a first-year entry-level mechanics course of 3 ECTS credits in an engineering program at a Belgian university. The student’s expectations in terms of learning objectives, learning activities, and type of assessment are investigated, because these are three essential components that a teacher uses to design a learning environment (Dijk et al., 2020). Additionally, it seeks to understand the effort students expect to put into the course as well as the effort they have put into it. Knowing the expectations of students regarding these components enhances the understanding of students by teachers and is a first step in potentially better aligning the expectations of students and teachers. Alignment has the potential to improve the transition of first-year students from secondary education towards engineering education potentially improving learning outcomes and attrition rates. The following research questions are central to this study: 1. What do first-year engineering students expect to be (i) the learning objectives, (ii) useful learning activities, (iii) the type of assessment and (iv) the amount of effort to succeed in an entry-level mechanics course? 2. How do the expectations of (i) and (ii) change throughout the semester? 2 METHODOLOGY To answer the above research questions, a quantitative research method based on a survey was chosen. The survey instrument was developed through a comprehensive literature review and in collaboration with field experts. It was validated through a pilot study, student interviews and statistical analysis (Heylen et al., 2025). The survey is administered three times, at the beginning, middle, and end of the semester to identify trends in students’ expectations. Therefore similar questions are repeated each time, or slightly adapted, and some specific questions are added depending on the timing, always keeping the survey under ten minutes to complete. Ethical approval was granted by the Social and Societal Ethics Committee of KU Leuven under approval number G-2023-6896. To investigate students’ perceptions of the learning objectives, a list of 13 learning objectives was scored on a 4-point Likert scale ranging from ‘Not at all important’ to ‘Very important’. The list was drafted by examining comparable courses' learning objectives and ensuring exhaustiveness by referencing Bloom's taxonomy (Krathwohl, 2002). Students' perceptions were assessed at the start, middle, and end of the semester to track changes. Similarly, to investigate students’ perceptions of the utility of learning activities, a list of 16 learning activities was scored on a 4-point Likert scale ranging from ‘Not at all useful’ to ‘Very useful’. The list was identified by analysing the course components and applying them to the cognitive dimension of Bloom's taxonomy. Students' perceptions were assessed at the start, middle, and end of the semester to track changes. At the end of the semester, students were also asked to rate the same learning activities on a 3-point Likert scale based on how much they actually used each activity. In the middle of the semester, after students had gained a reasonable impression of the course, they were asked how they thought the exam would look like. They rated 11 types of exam questions on a 4-point Likert scale ranging from ‘Not likely’ to ‘Very likely’ based on how likely they thought each question type would appear on the exam. Moreover, at the start and end of the semester, students were asked how much time they expected to put in and how much time they actually had put in the course, respectively. Students were instructed to include the time spent attending lectures and exercise sessions if applicable. Responses indicating more than 20 hours per week were discarded. Additionally, students were asked how much more time they expected to dedicate to the course during the examination period. The surveys were distributed among the first-year engineering students at a Belgian university campus, which offers both a program in Dutch and English. A researcher presented the online survey to the students during the lectures at three different occasions in the academic semester. The students were given ten minutes to complete it. Additionally, all students received an email invitation to fill the survey, so that also students who were not present in class had a chance to participate. To analyse the students’ responses to the Likert scale questions, scores ranging from 1 to 4 were assigned to the different response options. Subsequently, the average score for each item was calculated, along with the percentage of students who responded positively (scores of 3 or 4) to each item. Rankings were created for all questions based on both the average score and the percentage of students scoring the items positively. For the question regarding which learning activities students used, that was scored on a three-point Likert scale, scores of 1 to 3 were assigned to the respective categories and the average scores were calculated. A ranking for this question was made solely based on the average score. To identify significant changes in the perception of learning objectives and the expected utility of learning activities, the Friedman test was performed on the responses from students who completed the survey at all three time points. 3 RESULTS 399 students from in total 678 students, international (NENG=304) and Dutch (NDUT=374) speaking students combined, completed at least one of the three surveys. 294 students (NENG/ NDUT =208/86) completed the survey at the start of the semester, 185 students (NENG/ NDUT =133/52) completed the survey at the middle of the semester and 222 (NENG/ NDUT=112/110) students completed the survey at the end of the semester. In total 90 students (NENG/NDUT =68/22) took part in all three surveys. Learning objectives Table 1 presents the average scores and the percentage of students who rated the learning objectives as important. Both metrics are accompanied by a ranking, repeated for all three time points. At the start of the semester, students tended to score all learning objectives, except for ‘You are able to relate physics concepts not seen in class to concepts seen in class’, above 3.1 on average. As the semester progresses, the difference between the highest and lowest average scores for the learning objectives increases. Table 1. The perception of the learning objectives by students throughout the semester. Learning objective: “You are able to …” Av. scores Av. ranking % scores % rankings Start Middle End Start Middle End Start Middle End Start Middle End reproduce definitions and formula's 3.14 3.18 3.05 11 10 10 80.6 84 85.9 9 11 9 explain definitions and formula's 3.41 3.33 3.08 7 7 9 78.4 90.1 92.4 10 9 7 recognize situations to which the concepts (physics principles) covered in class apply 3.57 3.57 3.6 2 1 1 95.9 98 97.3 2 3 2 explain solution methods 3.41 3.44 3.32 7 4 6 91.4 93.9 95.7 6 5 3 apply definitions and formula's to new situations 3.58 3.49 3.54 1 2 2 95.9 98.3 95.7 2 2 3 employ physics theories and principles to explain phenomena in new scenarios 3.35 3.28 3.23 9 9 7 83.8 90.4 89.2 8 8 8 perform the necessary math calculations and operations 3.52 3.32 3.23 4 8 7 85.6 92.5 85.9 7 7 9 execute solution strategies to tackle problems in different situations 3.52 3.49 3.48 3 2 3 97.3 98.6 98.4 1 1 1 compare and contrast different theories and definitions 3.01 2.89 2.95 12 12 11 74.8 77.1 70.8 11 12 12 combine theories and physics' principles from different topics covered in class 3.42 3.35 3.45 6 6 4 93.2 93.9 93 5 5 6 combine and apply solution methods from different topics to new situations 3.43 3.37 3.44 5 5 5 94.1 95.9 95.1 4 4 5 relate physics’ concepts not seen in class to concepts seen in class 2.89 2.81 2.67 13 13 13 56.3 71 67 13 13 13 support your ideas about topics covered in class with arguments and examples 3.2 3.03 2.88 10 11 12 70.7 85.7 79.5 12 10 11 The most important perceived learning objectives are ‘You are able to …’: ‘recognize situations to which the concepts (physics principles) covered in class apply’, ‘apply definitions and formulas to new situations’, ‘execute solution strategies to tackle problems in different situations’ and ‘combine and apply solution methods from different topics to new situations’. All four objectives consistently scored high throughout the semester, both in terms of their average scores and the percentage of students who found them important. Learning activities Table 2 provides the average scores of the sixteen different learning activities and the percentage of students indicating each learning activity as useful. Both metrics are accompanied by their respective rankings, repeated for all three moments. The highest scores at the start and middle of the semester are 3.56 and 3.43, respectively, while the highest average score at the end of the semester is 3.06. Conversely, there is an increase in the percentage of students indicating those learning activities as useful. Table 2. The expected utility of the learning activities throughout the semester. Learning activity Av. scores Av. ranking % scores % rankings used Start Middle End Start Middle End Start Middle End Start Middle End Av. Rank Learning formulas and definitions by heart 2.59 2.57 2.36 15 16 14 53.6 59 52.2 14 14 16 2.03 14 Compare, contrast or derive formulas and definitions 3.34 3.08 2.73 6 11 11 71.2 90.8 82.6 11 5 10 2.13 11 Summarize or make a scheme of concepts and principles 3.41 3.32 2.84 3 5 6 74.3 91.8 91.8 9 4 3 2.03 9 Compare and contrast concepts and principles or apply them to real world examples 3.53 3.23 2.69 2 7 12 69.8 94.5 87 12 1 8 1.99 12 Learning concepts and principles by heart 2.57 2.61 2.28 16 14 16 50.5 51.5 58.7 15 16 14 1.91 15 (Re)reading formulas and definitions 2.91 2.74 2.69 13 13 13 69.4 72 65.2 13 13 13 2.14 13 Make exercises with support from the solution or others 3.29 3.41 2.98 9 2 4 76.1 86.3 90.2 6 9 5 2.21 6 Compare and contrast methods and techniques or explain them to others 3.41 3.38 2.96 3 4 5 82 93.9 94.6 1 3 1 2.16 1 Learning methods and techniques by heart 2.61 2.58 2.3 14 15 15 50 55.6 56.5 16 15 15 1.8 16 (Re)reading concepts and principles 2.94 2.91 2.73 12 12 10 73.9 75.8 77.2 10 12 12 2.23 10 Summarize methods and techniques 3.34 3.26 2.83 6 6 7 74.8 89.8 89.1 7 6 7 2.1 8 Explain your solution of an exercise to others 3.56 3.43 3 1 1 3 80.6 94.2 90.2 3 2 5 2.13 3 Reading examples of methods and techniques 3.19 3.22 2.83 10 9 8 79.7 85.7 90.8 4 10 4 2.27 4 Looking at example exercises 3.41 3.41 3.06 3 3 1 82 89.4 94 1 7 2 2.25 2 Summarizing or making a scheme of formulas and definitions 3.32 3.19 2.83 8 10 8 74.8 88.4 85.9 7 8 9 2 7 Make exercises without the support from the solution or others 3.13 3.23 3.05 11 8 2 79.3 76.1 81 5 11 11 2.29 5 Contrary to the high average scores for the highest-ranked learning activities at the start of the semester, the percentage of students expecting those learning activities to be useful is 82%. However, at the middle and end of the semester, the highest percentages of students expecting a certain learning activity to be useful are substantially higher, at 94.5% and 94.6%, respectively. The learning activities expected to be most useful across the whole semester are ‘Summarize or make a scheme of concepts and principles’, ‘Make exercises with support from the solution or others’, ‘Compare and contrast methods and techniques or explain them to others’, ‘Explain your solution of an exercises to others’ and ‘Looking at example exercises’. The learning activities expected to be the least useful are ‘Learning formulas and definitions by heart’, ‘Learning concepts and principles by heart’, ‘(Re)reading formula's and definitions’, ‘Learning methods and techniques by heart’ and ‘(Re)reading concepts and principles’. At the end of the semester, students were asked which learning activities they actually used, rated on a 3-point Likert scale. The average scores are indicated in the last two columns of Table 2. Students reported that they mostly engaged in exercises without support, read examples of methods and techniques, looked at example exercises, (re)read concepts and principles, and made exercises without support. There appears to be a mismatch between the usage of five learning activities and their perceived usefulness based on the relative rankings. ‘(Re)reading concepts and principles’, ‘Making exercises without support from solutions or others’, and ‘Reading examples of methods and techniques’ were used more frequently than they were perceived to be useful. Conversely, ‘Summarize or make a scheme of concepts and principles’ and ‘Explain your solution of an exercise to others’ were expected to be useful but were not used as much compared to other learning activities. Changing perception Looking at the 90 students that completed all three surveys, the learning objectives for which the perception changes significantly are ‘You are able to …’: ‘explain definitions and formulas’, ‘perform the necessary math calculations and operations’, ‘combine theories and physics’ principles from different topics covered in class’ and ‘support your ideas about topics covered in class with arguments and examples’. Except for ‘combine theories and physics’ principles from different topics covered in class’ the perception of these learning objectives decreases. The expected usefulness of six learning activities decreases significantly according to the Friedman test: ‘Compare, contrast, or derive formulas and definitions’, ‘Summarize or make a scheme of concepts and principles’, ‘Compare and contrast concepts and principles or apply them to real-world examples’, ‘(Re)reading formulas and definitions’, ‘Compare and contrast methods and techniques or explain them to others’ and ‘Explain your solution of an exercise to others’. Although the expected utility of ‘Explain your solution of an exercise to others’ significantly decreases, it remains one of the highest-scoring learning activities. Expected type of exam questions Table 3 presents the results of the question regarding the types of questions students expected on the exam. The average score (on a 4-point scale) and the percentage of students expecting each type of question are denoted, along with their respective rankings. The type of question most expected by students is ‘Problems (computation, etc.) combining different topics’, with 98.4% of students anticipating this kind of question. The second and third most expected types of questions are ‘Questions connecting different parts of the theory’ and ‘Visualizing/sketching a concept’. The least expected types of questions are ‘True/False questions’ and ‘Oral questions’. Notable is that the latter is indicated by 25.5% of the students as likely while from class one it was made clear that the exam contains problems containing problems on one or multiple topics combined. Table 3. The expected type of questions on the exam. Scores Ranking Type of questions Av. % Av. % Questions of the reproducing kind 2.61 60.9 8 6 Questions connecting different parts of the theory 3.30 86.4 2 2 Problems (computation, …) for each topic separately 2.71 59.7 5 8 Problems (computation, …) combining different topics 3.68 98.4 1 1 Elaborating on a topic 2.68 60.3 7 7 Multiple choice exercises 2.88 70.1 4 4 Multiple choice theory questions 2.69 63.0 6 5 Oral questions 1.84 25.5 12 12 Visualizing/sketching of a concept 3.24 85.33 3 3 True/false questions 1.98 26.1 11 11 Providing a derivation of a formula 2.59 54.9 9 9 Other 2.39 49.4 10 10 Effort At the start of the semester, students expected on average to dedicate 5.87 hours per week to this course, with a median of 5 hours per week. At the end of the semester, students reported spending an average of 3.96 hours per week, with a median of 3.5 hours per week. A dependent t-test comparing the responses of students who answered this question at both time points showed a significant difference (t=5.74, p<0.01). Additionally, the students expect on average to spend another 3.89 days (median of 4 days) of 9 hours studying in the examination period. 4 DISCUSSION AND CONCLUSIONS This exploratory study sketches a first image of what first-year engineering students expect regarding the learning objectives, useful learning activities and the type of assessment. This was done in the context of an entry-level mechanics course. The students found the learning objectives that emphasize the application of what they learned in class in new situations as most important. To achieve this, the students indicated that making summaries or schedules, comparing different methods, making exercises with support, looking at examples or explaining their solution to a problem as the most useful learning activities. At first glance, students seem to know that in order to arrive at the understanding and applying level of Bloom’s taxonomy they should as well study that way (Krathwohl, 2002). This is confirmed by the fact that learning activities focusing on remembering were expected to be the least useful. However, when comparing the learning activities that the students actually used with the learning activities that students anticipated to be useful, two learning activities that focus on remembering were actually used more than expected. A possible explanation for this is that to arrive at the learning activities that focus on understanding and applying the students need to have a firm basis of memorization, as indicated by Hattie & Donoghue (2016). Further mismatches between what learning activities the students used and the learning activities the students expected to be useful can be explained by practical limitations. The support that teachers can provide to students is limited and, while studying at their own pace, students cannot always explain their solution to others. On the other hand, those mismatches might indicate opportunities for the teaching staff to further improve the course. At the start of the semester the students score all learning objectives highly while for each learning activity there is almost 20% of the students who do not find it useful. These findings confirm that students indeed have their own preconceived notions about teaching methods and approaches to coursework at the start of university. Moreover, the difference between the highest-ranking and lowest-ranking learning objectives increases throughout the semester. Similarly, the agreement on which learning activities are useful also increases. These trends together with the significant changes in perfection of some learning objectives and learning activities show that students need some time to become accustomed to the new teaching approach at university and highlight the need for students to become better aware of what is expected from them (Hattie & Donoghue, 2016). In line with the learning objectives and learning activities students find most important and useful, halfway the semester, the type of exam questions students expect the most are problems combining topics. The fact that the least likely type of question ‘Oral questions’ is still indicated as likely by 25.5% of the students indicates that halfway the semester there is still ambiguity among students on how the exam will look like. Here lies an opportunity for better alignment between students’ and teachers’ expectations and consequently for students to adapt their study methods. Asking the students how much time they anticipate to spend on the course during the semester and comparing that to how much time they actually have spent on the course shows a significant overestimation. Given the three ECTS credits assigned to the course, a typical student should be able to pass the course with between 75 and 90 hours of work in total (ECTS Users’ Guide, 2015). At the start of the semester, the students are on average above this number while at the end of this semester their estimation is in line with these guidelines. Limitations and future work The whole group of first-year engineering students from both the Dutch and the English program is most likely to be heterogenous. This study did not look into these differences in background between students but will do so in future work. Additionally, the surveys were only completed by a subset of the total students population. Another difficulty in establishing a view on the expectations of students is which metric to use. In this study a choice was made to calculate the average score and the percentage of students that answered a Likert scale item positively. It is possible to come up with different metrics, like the median, which could have an influence on the results and conclusions. Future work will also look at data triangulation with more qualitative data to strengthen our understanding of student expectations. As another consideration, it should be noted that the students were asked to indicate how useful they thought different learning activities were to them at three different moments in time. However, the course consists of different topics, so students might be in multiple phases of learning at the same time for the different topics. This might make it difficult for them to specify which learning activities are most useful at one specific moment since for the different topics they could be at different phases of learning (Hattie & Donoghue, 2016). Lastly, the results from the survey give an insight into the expectations that exist among students. However, the impact of those expectations on the students’ learning outcomes was beyond the scope of this study. As next steps, the survey