Abstract

Undergraduate research experiences (UREs) have long been integrated into the landscape of undergraduate education, and the typical, one-on-one model has been associated with several positive student outcomes. Newer models of URE, aimed at improving scalability and promoting access for larger cohorts of students, have proliferated. However, due to the absence of a systematic classification of the models of UREs, comparisons across model types are limited, particularly in Canada. Therefore, it is unclear if these scalable models have achieved the aim of providing a more accessible, but equally impactful URE. We used principal component analyses of key variables derived from the course syllabi of 76 UREs to generate a typology of curriculum-based biology UREs, categorized into the following: Type A (apprenticeship-style research), Type B (field courses), and Type C (high enrollment, course-based research). Analysis of the course characteristics of these three course types revealed that Type C courses were the best positioned to provide an accessible learning environment and to include students who would otherwise not participate in research. The development of a typology of UREs provides a foundation to extend previous research on undergraduate research courses—which primarily focuses on the apprenticeship model—to include the other course types characterized in this study.

Graphical Abstract

Introduction

Pedagogies that engage students in the processes of science and promote scientific literacy are integral to undergraduate science education. Undergraduate research experiences (UREs) are proposed to be one such pedagogy (Brew 2006). The typical model of URE, where students conduct a research project under the supervision of a more experienced researcher (e.g., a graduate student, postdoctoral fellow, or faculty member), has been associated with an increase in both student engagement and academic success (Kuh 2008). Students who engage in UREs report a range of positive outcomes including cognitive and professional gains such as a greater understanding of the research process (2004; Seymour et al. 2004; Lopatto 2007), and an improved understanding of career options (Seymour et al. 2004; Lopatto 2007; Carter, Mandell, and Maton 2009; Adedokun et al. 2013), as well as affective gains such as increased self-confidence and resilience (Adedokun et al. 2013; Perrella et al. 2020), enjoyment of research (Seymour et al. 2004), and clarity of career aspirations and interests (Lopatto 2007; Adedokun et al. 2013). This may be in part due to the greater opportunity for high-quality student–faculty interaction as compared to lecture courses where only about one-third of students ever interact with their instructor (Bingham et al. 2022). These reported benefits to students are also supported by faculty (Hunter, Laursen, and Seymour 2007).
Furthermore, UREs have been shown to be especially beneficial for students from historically underserved groups (Haeger and Fresquez 2016) with an increase in the proportion of those who enter into a scientific career after graduation (Hernandez et al. 2018). These benefits are proposed to be a result of the mentoring and networking relationships that are fostered through this model and the self-efficacy and identity that these students develop as a result (Chemers et al. 2011; Byars-Winston et al. 2015; Alneyadi et al. 2019; Chaari et al. 2020). UREs are designated as a “high impact practice” by the Association of American Colleges and Universities (AAC&U) and are promoted as a core aspect of undergraduate science education (G. D. Kuh 2008; Lopatto 2010).
The one-to-one ratio of the apprenticeship model of URE limits the number of students who can participate. With calls to make UREs accessible to a greater number of students, educators have been challenged to broaden the conceptualization of how undergraduate research occurs to better serve more students (Healey 2005; Brew 2006; Jenkins and Healey 2009). Scalable models of URE developed to meet this challenge go by many names, including discovery research courses, course-based research experiences (CREs), and authentic laboratory undergraduate research experiences (ALUREs). In the North American context, they are collectively referred to as course-based undergraduate research experiences (CUREs) (Auchincloss et al. 2014) due to their large class design and their origins in UREs.
When compared to UREs, CUREs have a greater potential for access by large cohorts of students, due to larger class sizes. Furthermore, initial assessments of the learning value of CUREs have supported many of the same benefits as apprenticeship-style UREs (Toma et al. 2015). As a result, CUREs have proliferated across a range of disciplines in the US, with published examples of CUREs being most prevalent in the life sciences and biology (Dolan 2016; Buchanan and Fisher 2022). However, CUREs have also been implemented with similar effects in the social sciences (Ruth, Brewis, and SturtzSreetharan 2023) and business (Burga et al. 2023). A survey of Canada's UREs in the life sciences supports the recent uptake of CUREs within the Canadian context, with 13 of the 20 institutions reporting at least one high-enrollment research course which met the CURE criteria (Sun, Graves, and Oliver 2020).
Yet, research on the range of CURE types and their influences on student learning remains limited, particularly in the Canadian context. With the publication of a recent systematic review of 220 CURES, demonstrating broad use in different fields of STEM (Buchanan and Fisher 2022), the absence of a systematic characterization or classification of the models of UREs (which includes CUREs) limits the ability to compare across URE types, and results in most studies focusing on the evaluation of a single course at a single institution. As a result, attempts to validate new formats of UREs as equal to the apprenticeship model have lacked generalizability, making it unclear if these new, scalable models have achieved the aim of providing a more accessible, but equally impactful URE.
In this paper, we use factors related to course structure and assessment structure derived from course syllabi to describe a range of for-credit UREs and to propose a URE typology. The factors included in our analysis represent proven determinants of course impact such as investment of time and effort, and opportunities for substantive interactions with peers and mentors (G. Kuh, O'Donnell, and Schneider 2017), and factors impacting accessibility such as timing and cost. Recognizing that the range of UREs and level of resourcing is different across disciplines and in different educational jurisdictions, we focus on describing the UREs that currently exist in university biology programs in Ontario, Canada. This systematic classification of UREs based on shared features provides an essential foundation for future research.

Defining undergraduate research

We used an operational definition of undergraduate research informed by Lopatto (2003), Griffiths (2004), and Auchincloss et al. (2014; see Fig. 1) and most recently used by Buchanan and Fisher (2022) in their systematic review of CUREs. Specifically, we define UREs as experiences that engage students in intensive activities that mirror the processes of research and meet the five elements of UREs outlined in Auchincloss et al. (2014): (1) engagement in scientific practices, (2) exploration of questions with unknown answers to expose students to the process of scientific discovery, (3) examination of topics with relevance that extends beyond the course, (4) collaboration (with either peers or mentors), and (5) authentic “messy” data that demonstrate the iterative processes of science. The specific course formats, components, and teaching practices by which these are achieved can vary substantially in terms of purpose, accessibility, and structure (Beckman and Hensel 2009).
Fig. 1.
Fig. 1. Summary of relevant literature related to the key characteristics used to define the course formats by which undergraduate students engage with research. Broadly, there are four ways that research and teaching intersect, known as the research–teaching nexus, as described by Griffiths (2004): Research-informed, Research-led, Research-oriented, and Research-based. Traditional laboratories and methods courses are better described as “Research-oriented” in that they place emphasis on methods and the foundational knowledge derived from previous research, as opposed to the exploration and inquiry process. UREs and inquiry laboratories are best described as “research-based” courses as the curriculum is designed around exploring scientific practices and practicing inquiry, rather than learning subject content. UREs are differentiated from inquiry laboratories in that UREs involve the examination of topics with relevance that extends beyond the course, while inquiry courses focus on challenging students to engage in inquiry, regardless of the question (Auchincloss et al. 2014). CUREs and apprenticeship-style UREs can be further differentiated based on class size, admission processes, and scalability.
Some literature on UREs includes both traditional and inquiry-based laboratory courses within their operational definition. Traditional laboratories are those which are methods-driven, presenting content that is instructor-defined and pre-determined, with outcomes that are known to both students and to the instructor (Auchincloss et al. 2014). Inquiry laboratory courses differ from traditional laboratories as they focus on challenging students to explore genuine scientific thinking and to generate their own methods, while seeking to answer questions with answers that are unknown to both the instructor and students (Auchincloss et al. 2014; Sun, Graves, and Oliver 2020). Though the Auchincloss et al. (2014) model of essential elements was specifically developed for CUREs, they are broadly applicable to UREs and we refer to them interchangeably here.  By design, our definition excludes both types of laboratory courses, as neither course-type meets all five of the essential elements of UREs as defined by Auchincloss et al. (2014). While inquiry laboratories place emphasis on challenging the students to inquire in general, they do not necessarily require the students to ask questions that have relevance beyond the course.
Additionally, for the purposes of this research, we focussed exclusively on undergraduate research courses that were embedded in the curriculum and offered for credit, though there are a range of extra-curricular and non-credit opportunities, including volunteering, co-op positions, summer research fellowships, and other employment which could offer elements of or entire UREs but are not strictly required to (Beckman and Hensel 2009; Sun, Graves, and Oliver 2020). Notably, our study of for-credit courses includes honours theses that, unlike the United States but similar to both the UK and Australia, are offered as research courses within the curriculum.
The course characteristics used to describe the UREs investigated in this study were guided by both observed differences in characteristics derived from the course syllabi and existing frameworks of course descriptors in the literature. Specifically, Beckman and Hensel (2009) summarized several continua along which institutions may define undergraduate research models that differ in purpose, accessibility, and structure. For instance, UREs may be process-centered or outcome/product-centered, individual, or group-based, and/or they may be broadly available to all students or reserved for the students with the highest level of academic achievement. These continua, along with characteristics derived from the course syllabi, were used to characterize and describe the UREs offered in biology programs at 14 universities in Ontario, Canada.

Methods

Research overview and context

The post-secondary context in Ontario consists of 21 publicly funded universities (20 primarily English speaking and 1 exclusively French speaking), of which 18 offer a BSc program in Biology. This research will focus on 14 of these institutions, which represent the diversity of the Ontario post-secondary context (see Table 1). These 14 universities were selected because they are active members of the Ontario Universities Program in Field Biology (OUPFB), which is a collaborative initiative across Ontario universities to pool field course resources. The OUPFB allows students from one institution to enroll in field courses offered by other member institutions without having to transfer credits. All field courses offered through the OUPFB include an intensive research project component, and therefore it is convenient to sample from member institutions. The student population of these universities ranges from 7900 to 87 000 and they are located in both major cities and smaller regional centres. Three of these institutions offer primarily undergraduate programs, while the other 11 have comprehensive programs that offer undergraduate, graduate, and professional degrees and have substantial research activity.
Table 1.
Table 1. List of all Ontario universities included in this study.
Ontario universities included in this study (their 2021 full-time undergraduate enrollment)
Brock University (15 400)Queen's University (23 000)
Carleton University (20 200)University of Toronto (69 000)
University of Guelph (23 100)Trent University (9800)
Lakehead University (5800)University of Waterloo (35 200)
Laurentian University (5400)Western University (33 100)
McMaster University (30 300)Wilfrid Laurier University (16 500)
University of Ottawa (34 000)York University (41 900)

Data collection

For-credit UREs in undergraduate biology courses were included in this study. A database of these research courses was developed by reviewing the 2019 course calendars for the biology program(s) at each institution for courses that included the search terms “research”, “project”, “group”, “field”, “laboratory”, or “thesis” in their posted course description. The OUPFB course offerings were also included as all of these courses require a research project to be completed while on the field course. This process resulted in 80 undergraduate biology research courses across all 14 universities. We obtained the syllabus for each course from either publicly available online databases or by contacting course faculty or administrative staff by email. We restrict our analysis to syllabus information only because these documents are publicly available and most immediately accessible to all students. Several courses did not have a standard syllabus as some or all of the components of the course were to be negotiated between the student and their supervisor. In these cases, we contacted the faculty or administrator who coordinated the course most recently to obtain the required information where available. One course was removed from analysis because a department administrator indicated that it was not regularly offered, no faculty had recently taught it, and no syllabus existed. Two course codes were removed because they accounted for programs that were too variable to be captured in this analysis. Research experiences that required two courses to be taken sequentially or concurrently were included only once.
The collected syllabi (n = 77) were reviewed to ensure that the courses met the stated operational definition of engaging students in intensive activities that mirrored the process of research and included the five elements of UREs outlined in Auchincloss et al. (2014). Typically, this constituted courses that included a substantial lab- or field-based project requiring students to work independently or as a member of a group to develop research questions, to organize and/or analyze data, and to disseminate the results of their research. In many courses, this process also involved data collection; however, courses where students worked with previously collected data were also included. One course was removed from the initial database because the project referenced in the course description was described as a series of lab assignments instead of a cohesive research project.
Of the 76 undergraduate biology research courses included in this study, we collected complete information for 15 variables of interest from 62 courses by consulting the syllabus and/or the course faculty/administrators. Variables related to the relative weight of the assessments (seven variables) were missing from 14 courses, because these courses allowed students to negotiate the weight of their assignments with their instructors. Eight variables were still collected for these courses by consulting with course faculty/administrators.

Description of variables

The variables used in the analysis are described in Table 2.
Table 2.
Table 2. Rationale for course variables included in analysis.
VariableRationale
Credit worthCaptures the intensity of the course
Length in weeksCaptures the intensity of the course
Cost (CAD$) in addition to tuitionPossible barrier to access; implications for enrollment
Semester offeredPossible barrier to access if course is offered exclusively outside of the academic year (i.e., during the summer semester); implications for enrollment
Min. grade requirementCaptures the degree to which enrollment was competitive; possible barrier to access
Application requirementCaptures the degree to which enrollment was competitive; possible barrier to access
Student:staff ratioCaptures the course format (large class, small class, one-on-one); captures the opportunity for substantive interactions with faculty.
% grade from group workCaptures the course format (individual vs. group-based) and the opportunity for substantive interactions with peers

Course descriptive variables

Eight variables were collected from the syllabi for all 76 research courses to characterize the courses based on their format: (1) credit worth, (2) length in weeks, (3) cost in addition to tuition, (4) semester offered, (5) minimum grade requirement, (6) application requirement, (7) number of students per staff, and (8) % of grade from group work.
Course characteristics were derived from the syllabi to differentiate the courses based on several continua along which institutions may define undergraduate research models. For instance, UREs may be individual or group-based, and they may be broadly available to all students or reserved for the students with the highest level of academic achievement (Beckman and Hensel 2009). Elements that could constitute barriers to access were also identified and included as variables. As these variables were derived from the syllabi, the range of variables was limited by which variables were available across all or most syllabi included in the analysis. The rationale for each of the variables included in this analysis is described in Table 2.
The credit value of courses was standardized to a 2.5 credit full-time semester. This was based on the credit system at the University of Guelph, where most single semester courses have a credit value of 0.50 and a full-time course load is typically 2.50 credits per semester and 5.00 credits per academic year. Among the study institutions, this credit system is shared with Brock University, Carleton University, Lakehead University, Trent University, University of Toronto, University of Waterloo, Western University, and Wilfrid Laurier University. Laurentian, McMaster, Queens, Ottawa, and York Universities follow a credit system where full-time enrollment is 15 credits per semester. Therefore, the course values at these institutions were divided by 6 for the analysis (i.e., a 3.00 credit course is the equivalent of a 0.50 credit course). The length of the course in weeks was also included to capture the intensity of the course.
The courses offered through the OUPFB typically occur off campus and therefore they are offered at an additional cost to students. Some non-OUPFB courses also charge a small fee in addition to tuition for the cost of field trips and course resources. These additional fees were included as a variable. The timing of course offerings as during the typical academic year (i.e., fall and winter semesters) or in the summer semester is also an important variable because courses offered only in the summer may not be accessible to students who rely on summer employment to pay for their education. Courses that were offered during the academic year were recorded as “yes”, while those offered exclusively outside of the typical academic year were recorded as “No”.  The primary location of course instruction (on-campus vs. off-campus) was also initially included but was determined to be redundant to the “academic year vs. summer semester” variable, as all courses that occurred during the academic year occurred on campus, while all those which occurred at an off-campus field site, occurred exclusively during the summer semester.  Therefore the “campus vs. off-campus” variable was removed.
Many research courses have competitive enrollment and only a small subset of students are accepted. The degree to which enrollment was competitive was captured by whether there was a minimum grade required for enrollment (yes and no) and if an application was required to enroll (yes and no).
The ratio of students per teaching staff was used to capture the capacity for frequent student interactions with staff. In courses where a student was working directly with a supervisor, the class size was recorded as one. In all other instances, the class capacity was divided by the number of instructors listed on the course syllabus, plus one teaching assistant (assumed, unless otherwise stated). Student interactions with peers is also an important course variable, and so the capacity for these interactions was captured by the % of a student’s grade accounted for by group work.

Assessment variables

Seven variables related to assessment type were collected from the courses that had pre-determined assessments (n = 62). Therefore, 14 courses were excluded from this analysis as the weight and type of assessments were determined through negotiations between the instructor and the student and were therefore not available in the course syllabus. These courses were all apprenticeship-style courses where the student works one-on-one with the instructor to complete a research project. The seven assessment variables collected were: (1) the total number of assignments, (2) % of grade from oral presentations, (3) % of grade from written assignments, (4) the % of grade from reflective assignments or activities, (5) the % of grade from research effort/participation, (6) the % of grade from data entry or laboratory/field notes, and (7) the % of grade from quizzes or examinations. There were no examples of assessments that did not meet the criteria for one of these categories.

Statistical analysis

We used two categorical principal component analyses (PCA) to observe clustering of courses and to classify the research courses into types by each of the course descriptive variables and by the assessment variables. This approach is based upon an analysis of class size using course outline and enrollment data by Cash et al. (2017) and an analysis of the characteristics of residence learning communities derived from the websites of nine Canadian universities by Hobbins et al. (2016). PCA is a statistical tool used to reduce multi-dimensional data into fewer dimensions by creating component groups of correlated variables. By graphing the courses based on their scores on the first two principal components, clusters of courses are created allowing us to visualize the various groups. The PCA was performed using the FactoMineR and factoextra packages in R Statistical Program (R Core Team 2020). For the course descriptive variables, principal component 1 (51.2%) and 2 (21.7%) accounted for 73% of the variance in the dataset. The contributions of each variable to the course descriptive principal components are shown in Table 3. For the assessment variables, principal component 1 (25.2%) and 2 (23.9%) accounted for 49.1% of the variance in the dataset. The contributions of each variable to the assessment principal components are shown inTable 4.
Table 3.
Table 3. PCA scores of eight descriptive variables that were used to classify the characteristics of 76 research courses in Biology departments across 14 Ontario universities.
VariableBinary or numerical rangePrincipal Component 1 ScorePrincipal Component 2 Score
Credit worth0.5–20.69−0.24
Weeks2–240.92−0.22
Added cost ($)0–5500−0.720.33
Within the academic yearYes = 1; No = 00.83−0.34
Minimum grade requiredYes = 1; No = 00.70−0.16
Application requiredYes = 1; No = 0−0.040.93
Number of students per staff1–26−0.64−0.64
Grade from groupwork (%)0–80−0.640.49

Note: PCA, principal component analyses.

Table 4.
Table 4. PCA scores of seven assessment variables that were used to classify the characteristics of 62 research courses in Biology departments across 14 Ontario universities.
VariableNumerical rangePrincipal Component 1 ScorePrincipal Component 2 Score
Total number of assignments2–12−0.370.31
Grade from oral presentations (%)0–500.410.76
Grade from written assignments (%)20–1000.66−0.65
Grade from reflective assignments (%)0–15−0.470.05
Grade from participation/research effort (%)0–40−0.110.64
Grade from data entry or lab/field notes (%)0–35−0.79−0.23
Grade from quizzes/exams (%)0–45−0.43−0.33

Note: PCA, principal component analyses.

Results and discussion

The PCA scatterplot for the course variables (Fig. 2) showed distinct data clustering based on the scores of the first two principal components, which accounted for 71.5% of the variance in the data. Principal component 1 (PC 1) accounted for the greatest amount of variance in this data (48.1%) and nearly all of the variables contributed substantially to this dimension, with the greatest contributions from the length of the course in weeks, and whether the course occurred outside of the academic year. Only the requirement of an application to enroll in the course did not contribute to dimension 1. PC 2 accounted for 23.4% of the variance and was mostly determined by whether an application was required. The ratio of staff to students and the percentage of the grade which came from group work were also important contributors. The data clustered into three groups along these two dimensions. This analysis permits the development of a typology of curriculum-based undergraduate biology research experiences, categorized into the following: Type A, Type B, and Type C.
Fig. 2.
Fig. 2. Clustering of 76 biology research courses at Ontario universities based on the PCA obtained from eight variables describing characteristics of the courses. The graphical dispersion is then overlaid with labels of the course type assigned to each cluster (Type A—blue, Type B—green, Type C—orange) and 95% confidence ellipses plotted for each group. PCA, principal component analyses.
Fourteen courses did not have predetermined assessment weights, and so were excluded from the second PCA analysis. All 14 were categorized as “Type A” by the first PCA, where the student was working one-on-one with a faculty member and so could negotiate the assessment weights directly with their faculty supervisor. The second PCA analysis of the assessment variables (Fig. 3) accounted for a total variance of 49.1%. PC 1 accounted for slightly more variance in the data (25.2%), with less grading emphasis on lab/field notes and greater emphasis on written assignments, making the largest contributions to this dimension. PC 2 accounted for 23.9% of the variance and greater grading weight on participation and oral presentations and less weight associated with written assignments contributed to this dimension. When the typology from the previous PCA was overlaid onto the clustering of assessment variables, Type A and Type B courses clustered into two groups with Type C courses forming a bridge between them. This indicates that Type A and Type B courses use distinct assessment patterns and Type C courses use a range of assessment patterns that may resemble either of the first two types. However, the course clusters exhibited a lot of variability indicating variation both between course types and within them.
Fig. 3.
Fig. 3. Clustering of 62 biology research courses at Ontario universities based on the PCA obtained from seven variables describing characteristics of the assessments. The graphical dispersion is then overlaid with labels of the course type assigned to each cluster (Type A—blue, Type B—green, Type C—orange) and 95% confidence ellipses plotted for each group. PCA, principal component analyses.
Based upon the clustering analysis for both course characteristics and assessment types, we integrate these findings within the existing typology of UREs to provide finer detail on the accessibility of each (Fig. 4).
Fig. 4.
Fig. 4. Summary of how the typology outlined in this analysis fits into the previous literature on undergraduate research experiences (UREs). Key differentiating variables are bolded for clarity. Type A aligns closely with the typical apprenticeship model described in the literature. Type B and C both align with course-based research experiences (CUREs), as they are higher enrollment courses that fit within the formal curriculum. However, as Type B is competitive, expensive, and occurs outside of the academic year, it may not meet the scalability and accessibility requirements outlined in the CURE literature. Therefore, Type B courses are considered distinct from Type C courses, which aligns better with the existing literature on CUREs, in this typology.

Type A

Type A courses (N = 37, 49% of the sample) include courses in which a student works under direct, one-on-one supervision of an expert, usually a faculty researcher, to conduct authentic research in an area related to the researcher’s expertise. The Type A course model closely resembles the apprenticeship model described in the literature.
Type A research courses typically have a greater credit value and are more likely to be two semester courses. These courses are often called a “thesis project” or “independent study” in the course description and are nearly exclusively offered to upper year students. Research projects are completed independently and lack the group work component that is typical of other courses in this typology. Research in Type A courses may be lab, field, or literature-based and aims primarily to engage students in the processes of authentic research. Examples of learning goals include, “Students are expected to design a self-guided research question and project at the level expected for a fourth-year independent research project within the constraints imposed by the course” (BIOL 4522, University of Guelph) and “Students should be able to conduct research. Evaluate and analyze the data collected. Write and present a final thesis based on the research conducted.” (BIOL 4970 F, Western University). Students are usually expected to attend frequent meetings with their supervisor and the supervisor’s research group, which may result in a peer network comparable to the group assignments in other course types. In some cases, students are expected to take on additional responsibilities such as contributing to their labmates’ research projects and tidying/maintaining the lab space.
The process of enrollment in Type A courses can be very similar to a job application, “Since students are not just taking a course but are also collaborating in the research program of a faculty member, faculty make BIOL537 offers to students based on their applications.” (BIOL537, Queen's University). A total of 72.97% of Type A courses had a minimum GPA requirement to enroll, with requirements ranging from 63% to 80%, with a mean minimum GPA of 73%. Type A courses also always required some form of application to enroll; however, the application process ranges in intensity from simply having to meet the eligibility requirements (BIOL 4F90/4F91, Brock University) or finding a willing supervisor (BIO481, University of Toronto) to more extensive applications that may require a research proposal, a CV, an exemplary transcript, a cover letter, and/or academic references (BIO4009, University of Ottawa). Enrollment based on the discretion of a potential supervisor is also likely to involve a comprehensive application and “job” interview.
The weight and type of assessments in Type A courses are often negotiated between the student and supervisor (n = 14 in our sample). When pre-structured assessments do exist, they tend to have fewer assignments overall and are based on oral presentations, writing, and participation/professionalism/effort, as opposed to tests, lab/field notes, or reflective activities. However, there is a lot of variability in the total number of assessments (ranging from 2 to 12) and the relative weight of written works vs. oral presentations and participation, which tend to co-vary. Often scaffolding of writing instruction is built into the assessment structure, such that students are required to hand in drafts of writing for editing prior to the submission of their final written assignment.
In general, apprenticeship research courses act as an introduction to graduate research. Indeed, these courses are often geared specifically towards students who have an interest in pursuing graduate studies, “This course is strongly recommended for students contemplating graduate work in Biology, or who are interested in pursuing a career in research of any kind.” (BIO-4C12, McMaster University).

Type B

Type B courses (N = 31, 40.8% of the sample) are characterized by their scheduling outside of the academic year, additional cost, requirement for an application, and a higher student to advisor/instructor ratio than Type A courses. These courses are usually described as “field courses”. Most of these courses are offered through the OUPFB and are available to students at all 14 institutions; however, four of them are offered only by the University of Toronto (EEB 398H1, EEB 3981, EEB 3982, EEB 3983). While these four course offerings differed from the OUPFB courses in length (longer), and cost (no additional cost), they still fell within the field course cluster.
Type B courses are short, intensive courses offered during the summer semester at a field research site in Canada or abroad. In some cases, these sites may expose students to new and uncomfortable circumstances, “Biting insects (particularly mosquitoes and black flies) are present in extreme abundance at certain sites. It is absolutely essential to bring a high-quality bug jacket as well as pants that insects can't bite through.” (AEC, University of Guelph). Due to their short duration, Type B are very intensive, featuring long days with few breaks over the 2 week duration. Typically, students and faculty live on-site for the duration of the course and share meals and free-time together. In these cases, accommodations range from tents, to comfortable dormitory style residences, “Sleeping accommodations are student dorms (up to four in a room and gender specific).” (SEB, McMaster University). Students spend some portion of the first week of the course learning about the field site and working to develop research questions and hypotheses. During the second week of the course, students begin data collection and analysis for their independent or small group research project. Dissemination of the research results is usually due at a date several weeks to several months after the return from the field site.
Students are expected to take on additional responsibilities at the field site, including cooking meals, tidying common spaces, and assisting with ongoing research occurring at the research station. Finally, unlike other courses, there is an element of tourism included in Type B courses. Students may participate in whale watching on the East Coast of Canada (MBO, University of Guelph), safari in East Africa (BCE, Queen’s University), and snorkeling on a remote island in Belize (TME, Western University). This exploration of novel and exciting places is an intentional aspect of many of the field courses included in this analysis, “We designed the class to encompass the most beautiful places we know from this part of the world” (WEA, University of Ottawa).
The process of enrollment in Type B courses typically involves a competitive application. Students who have met the course prerequisites must submit an application specifying the top three OUPFB field courses of interest and their complete academic record. In some cases, students are also required to provide background on their past field and research experiences and their career goals. While some courses indicate that students who have met the prerequisites are enrolled on a first come, first serve basis, others indicate that the course instructors may select successful applicants from the application pool based on merit. While some of the applications do specify that enrollment may be based on a competitive GPA, no specific GPA requirements are stated. Unlike Type A and C courses, Type B courses typically come at an additional cost on top of tuition, to pay for accommodations, travel, and course resources. This additional cost can range from CDN$700 for relatively local field sites (TFB, University of Toronto) to over CDN$5000 for field sites overseas (WEA, University of Ottawa).
Relative to Type A courses, Type B courses are more likely to involve group work, perhaps due to larger class sizes. Importantly, while group work is associated with learning gains, we did not find evidence of a curriculum in skills related to group work in this study. The patterns of types and weights of assessments in field-based research courses were variable, with some Type B courses involving major written components and others being largely based on assignments related to keeping field or laboratory notes. Compared to Type A courses, Type B courses are more likely to be assessed via lab/field notebooks, reflective activities, and tests. Written assessments typically have less weight on final grades. Oral presentations are the least common/lowest weighted form of assessment during field courses overall.

Type C

Type C research courses (N = 8, 10.5% of the sample) were a less distinct course type in our sample, with relatively few exemplars and greater variability in course characteristics and assessment types. Type C courses were only found at four universities, including the University of Guelph, the University of Waterloo, Western University, and York University. We found that Type C courses are primarily characterized by not requiring students to apply to enroll. These courses also trend towards a greater student-to-staff ratio and a greater emphasis on group work. Therefore, the Type C classification best aligns with the CURE model described in the literature.
Type C courses are often described as “experiential learning” courses in the course description. Like other research courses, the goal of Type C courses is to provide students with an opportunity to participate in authentic research, as demonstrated by this learning outcome: “Plan and execute an independent field research project, from development of the experimental question or hypothesis to be tested, to design and implementation of the sampling or data acquisition, choosing the appropriate statistical or other analytical methods for the data or samples acquired, presenting the results graphically and in writing…” (BIOL 3230, Western University). However, unlike the other course types in this typology, Type C courses are built into the standard curriculum and allow students to conduct authentic research without having to meet GPA requirements or to apply for more competitive research opportunities. This is achieved by having larger class sizes, making enrollment non-competitive. The on-campus location of Type C courses also removes potential barriers associated with travel and living away from home, while participating in a Type B course, “Local field sites will be used to run in-course experiments” (BIOL 3010, University of Guelph).
Of the eight Type C courses included in our analysis, three focus primarily on field-based research (BIOL 3010 and BIOL 4110, University of Guelph; BIOL 3230; Western University), four focus primarily on lab-based research (IBIO 4600, University of Guelph; BIOL3250, York University; BIOL 349, University of Waterloo; BIOL 4998, Western University), and one did not specify the research approach, as the project involved collaborating with a community partner and could involve either laboratory or field work depending on each student’s specific project (IBIO 3100/4100, University of Guelph). The course formats are also quite variable, with some emphasizing lecture content (BIOL 3250, York University) and others focusing on experiential field excursions (BIOL 3230, Western University). Nearly all courses indicated that some lecture time would be spent discussing statistics, doing student presentations, and/or hearing guest speakers.
While the topics of research in other course types are often limited by the student’s ability to find an advisor or by the practical considerations of the field site, Type C research courses may be limited in scope by the course requirements. For instance, in BIOL3010 (University of Guelph), students are required to work in teams to investigate four research topics that are pre-determined by the instructors. While the scope may be limited, the learning outcomes in Type C courses include many of the same components as the other URE types, including planning and executing a research project and developing an appreciation for the process of research; “Learning outcomes: … To appreciate the diversity, beauty, intricacies and opportunities involved in conducting ecological research” (BIOL 4110, University of Guelph).

Limitations

Though this paper provides the first study to propose a comprehensive typology of UREs, there are several factors to consider in the interpretation of these findings. First, while an effort was made to collect data on the full range of research courses across all universities, it is possible that one or more courses that met our inclusion criteria were not included in our analysis simply because the course description did not include our key words. Additionally, this analysis aggregated several course types into a single typology, to produce more generalizable comparisons. However, a more detailed comparison of the courses that make up each type is also important, most notably for the courses categorized as CUREs, as they were the most variable and least well-defined in this research. Future work could consider interviewing the faculty designing and teaching CURE courses to provide a much clearer picture of the range of formats that exist within this course model.

Recommendations

While any commitment to increasing access to authentic research opportunities in an undergraduate program is valuable, it is important to recognize that the models are distinct. Instructors of Type A courses should ensure that the competitive application process is more transparent and accessible to all students. Reducing bias will increase the diversity of students who benefit from this high impact teaching practice. Instructors of Type B courses should work to reduce the cost of the experiences. This can be achieved by seeking out subsidies for travel-based courses and by offering a local field course experience. Type C courses are, by their characterization, a research experience stretched out over the semester. This reduces the cost to students and the resources of the department needed to implement them. Despite this, there were relatively fewer of these courses offered within the region. We recommend that more of them be developed and made available to students within their program requirements.
Because the syllabus is an accessible and informative document that can support students in making decisions about their academic pathway, we recommend providing access to these documents in advance of course selection dates and making them a more standardized format that includes common information types to allow for easier comparison.

Impact of COVID-19

These data were collected for courses offered in the 2019 academic year, prior to the COVID-19 pandemic which caused major disruptions to in-person post-secondary education in 2020 and beyond. With the onset of the pandemic, all field courses offered by the OUPFB were cancelled for both the 2020 and 2021 academic years. Most domestic courses were reinstated for 2022 and some international field experiences were offered in 2023. However, many long-standing field courses have yet to be reinstated, perhaps due to the perceived economic benefits of these cancellations for departments. The loss of these field courses for two academic cohorts and the diminished opportunities for future cohorts greatly reduces the capacity of UREs for Ontario biology undergraduates. Similarly, during the COVID-19 pandemic, opportunities to participate in Type A and Type C UREs were also greatly reduced. The impacts of the loss of these opportunities on student cohorts is a potential avenue for future study.
Many institutions sought to offer alternatives to in-person UREs during the COVID-19 pandemic, particularly by offering remote research experiences. For instance, one method used by instructors was to integrate modular research experiences into an existing large first year undergraduate biology course (Robertson et al. 2021; Porter et al. 2022). Another example of a remote URE was offered by the biology departments at the University of Guelph and York University. These departments collaborated to offer a fully remote field experience, where students would engage in remote, synchronous instruction, while conducting a group field research project in their own backyards and neighbourhoods. While this course was well-received, its impact has yet to be empirically compared to in-person versions. Indeed, the shift to online and remote learning, mandated by the COVID-19 pandemic, revealed a gap in the literature surrounding how to engage students in undergraduate research while working and learning remotely and the impact of these remote learning experiences compared to in-person offerings.

Conclusion

The goal of this paper was to generate the first evidence-based typology of biology UREs in Ontario by clustering URE courses at 14 different universities into types based on course characteristics. The data presented in this paper permit the development of a finer scale typology of curriculum-based undergraduate biology research experiences, categorized into the following: Type A, Type B, and Type C. The development of a typology of UREs provides a foundation to extend previous research on undergraduate research courses—which primarily focuses on the apprenticeship model—to include the other course types characterized in this study.

Acknowledgements

The Dish with One Spoon Covenant speaks to our collective responsibility to steward and sustain the land and environment in which we live and work, so that all peoples, present and future, may benefit from the sustenance it provides. As we continue to strive to strengthen our relationships with and continue to learn from our Indigenous neighbours, we recognize the partnerships and knowledge that have guided the learning and research conducted as part of this work. The University of Guelph resides in the ancestral and treaty lands of several Indigenous peoples, including the Attawandaron people and the Mississaugas of the Credit, and we recognize and honour our Anishinaabe, Haudenosaunee, and Métis neighbours.

References

Adedokun O.A., Bessenbacher A.B., Parker L.C., Kirkham L.L., Burgess W.D. 2013. Research skills and STEM undergraduate research students’ aspirations for research careers: mediating effects of research self-efficacy. Journal of Research in Science Teaching, 50(8): 940–951.
Alneyadi A., Shah I., Ashraf S.S. 2019. An innovative bioanalytical research project course to train undergraduate students on liquid chromatography-mass spectrometry. Biochemistry and Molecular Biology Education, 47(3): 228–238.
Auchincloss L.C., Laursen S.L., Branchaw J.L., Eagan K., Graham M., Hanauer D.I., et al., 2014. Assessment of course-based undergraduate research experiences: a meeting report. CBE—Life Sciences Education, 13(1): 29–40.
Beckman M., Hensel N. 2009. Making explicit the implicit: defining undergraduate research. CUR Quarterly, 29(4): 40–44. https://www.mcgill.ca/senate/files/senate/beckman__hensel_making_explicit.pdf.
Bingham B.E., Rea V., Robertson L., Smith M.A, Jacobs S. 2022. Frequency, topic, and preferences: Tracking student engagement with several modalities of student–instructor contact in a first-year course. FEBS Open Bio, 12(1):12–23.
Brew A. 2006. Research and teaching: beyond the divide. Palgrave Macmillan, New York.
Buchanan A.J., Fisher G.R. 2022. Current status and implementation of science practices in course-based undergraduate research experiences (CUREs): a systematic literature review. CBE—Life Sciences Education, 21(4): ar83.
Burga R., Spear C., Balestreri C., Boyle J., Coasley A., Mcgill D., et al. 2023. Enhancing management education: How do experiences outside the classroom matter? The International Journal of Management Education, 21(1): 100758.
Byars-Winston A.M., Branchaw J., Pfund C., Leverett P., Newton J. 2015. Culturally diverse undergraduate researchers’ academic outcomes and perceptions of their research mentoring relationships. International Journal of Science Education, 37(15): 2533–2554.
Carter F.D., Mandell M., Maton K.I. 2009. The influence of on-campus, academic year undergraduate research on STEM Ph.D. outcomes: evidence from the Meyerhoff Scholarship Program. Educational Evaluation and Policy Analysis, 31(4): 441–462.
Cash C.B., Letargo J., Graether S.P., Jacobs S.R. 2017. An analysis of the perceptions and resources of large university classes. CBE—Life Sciences Education, 16(2): 1–12.
Chaari A., Al‐Ali D., Roach J. 2020. Biochemistry course-based undergraduate research experience: purification, characterization, and identification of an unknown lactate dehydrogenase isoenzyme. Biochemistry and Molecular Biology Education, 48(4): 369–380.
Chemers M.M., Zurbriggen E.L., Syed M., Goza B.K., Bearman S. 2011. The role of efficacy and identity in science career commitment among underrepresented minority students. Journal of Social Issues, 67(3): 469–491.
Dolan E.L. 2016. Course-based undergraduate research experiences: current knowledge and future directions. Committee on Strengthening Research Experiences for Undergraduate STEM Students. pp. 1–34.
Griffiths R. 2004. Knowledge production and the research-teaching nexus: the case of the built environment disciplines. Studies in Higher Education, 29(6): 709–726.
Haeger H., Fresquez C. 2016. Mentoring for inclusion: the impact of mentoring on undergraduate researchers in the sciences. CBE—Life Sciences Education, 15(3): 1–9.
Healey M. 2005. Linking research and teaching to benefit student learning. Journal of Geography in Higher Education, 29(2): 183–201.
Hernandez P.R., Woodcock A., Estrada M., Schultz P.W. 2018. Undergraduate research experiences broaden diversity in the scientific workforce. Bioscience, 68(3): 204–211.
Hobbins J., Eisenbach M., Ritchie K.L., Jacobs S. 2016. Residence learning communities at Canadian comprehensive institutions. Teaching and Learning Innovations Journal, 18:1–26.
Hunter A.‐B., Laursen S.L., Seymour E. 2007. Becoming a scientist: the role of undergraduate research in student's cognitive, personal, and professional development. Science Education, 91(1): 36–74.
Jenkins A., Healey M. 2009. Developing undergraduate research and inquiry. The Higher Education Academy.
Kuh G. 2008. Why integration and engagement are essential to effective educational practice in the twenty-first century. Peer Review, 10(4): 27.
Kuh G., O'Donnell K., Schneider C.G. 2017. HIPs at ten. Change: The Magazine of Higher Learning, 49(5): 8–16.
Kuh G.D. 2008. High-impact educational practices: what they are, who has access to them, and why they matter. AAC&U, Washington, DC.p. 34.
Lopatto D. 2003. The essential features of undergraduate research. CUR Quarterly, no. March: 139–142.
Lopatto D. 2004. Survey of undergraduate research experiences (SURE): first findings. Cell Biology Education, 3(4): 270–277.
Lopatto D. 2007. Undergraduate research experiences support science career decisions and active learning. Cell Biology Education—A Journal of Life Science Education, 6: 297–306.
Lopatto D. 2010. Undergraduate research as a high-impact student experience. Peer Review, 12(2):27–30.
Perrella A., Dam H., Martin L., Maclachlan J.C., Fenton N. 2020. Between culture and curricula: exploring student and faculty experiences of undergraduate research and inquiry. Teaching & Learning Inquiry, 8(2): 90–113.
Porter E., Luo M.X., Lit B., McKechnie I., Saha J., Ratra P., et al. 2022. Developing a transdisciplinary citizen science tool for experiential learning in undergraduate education: squirrel life in a nutshell. In INTED2022 Proceedings. pp. 1781–1790. IATED.
R Core Team. 2020. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.r-project.org/.
Robertson L., Porter E., Smith M.A., Jacobs S. 2021. Evidence-based course modification to support learner-centered and student-driven teaching in a pandemic: leveraging digital and physical space for accessible, equitable, and motivating experiential learning and scientific inquiry in a first-year biology course. International Journal of Higher Education, 10(7): 96–109.
Ruth A., Brewis A., Sturtzsreetharan C. 2023. Effectiveness of social science research opportunities: a study of course-based undergraduate research experiences (CUREs). Teaching in Higher Education, 28(7): 1484–1502.
Seymour E., Hunter A.‐B., Laursen S.L., Deantoni T. 2004. Establishing the benefits of research experiences for undergraduates in the sciences: first findings from a three-year study. Science Education, 88(4): 493–534.
Sun E., Graves M.L., Oliver D.C. 2020. The Lay of the Land: an overview of Canada's undergraduate research opportunities within the life sciences. Scholarship and Practice of Undergraduate Research, 4(1): 63–71.
Toma S., Roth-Johnson E.A., Hancock S.P., Ayon C., Zimmerman H., Levis-Fitzgerald M. et al. 2015. Comparing the impact of course-based and apprentice-based research experiences in a life science laboratory curriculum. Journal of Microbiology and Biology Education,  16(2): 186–197.

Information & Authors

Information

Published In

cover image FACETS
FACETS
Volume 9January 2024
Pages: 1 - 12
Editor: Elena M. Bennett

History

Received: 25 January 2023
Accepted: 10 February 2024
Version of record online: 30 July 2024

Data Availability Statement

Data generated or analyzed during this study are available from the corresponding author upon reasonable request.

Key Words

  1. undergraduate research experience
  2. experiential learning
  3. biology education
  4. CURES
  5. field biology

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Plain Language Summary

What types of research experiences do students have access to during their undergraduate degree?

Authors

Affiliations

Department of Integrative Biology, University of Guelph, Guelph N1G 1Y2, Canada
Author Contributions: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Validation, Visualization, Writing – original draft, and Writing – review & editing.
K.L. Ritchie
Department of Human Health and Nutritional Science, University of Guelph, Guelph N1G2W1, Canada
College of Biological Science Office of Educational Scholarship and Practice, University of Guelph, Guelph N1G2W1, Canada
Author Contributions: Methodology and Writing – review & editing.
T.R. Gregory
Department of Integrative Biology, University of Guelph, Guelph N1G 1Y2, Canada
Author Contributions: Methodology, Resources, Supervision, and Writing – review & editing.
Department of Integrative Biology, University of Guelph, Guelph N1G 1Y2, Canada
College of Biological Science Office of Educational Scholarship and Practice, University of Guelph, Guelph N1G2W1, Canada
Author Contributions: Data curation, Funding acquisition, Methodology, Project administration, Resources, Supervision, and Writing – review & editing.

Author Contributions

Conceptualization: BEB
Data curation: BEB, SRJ
Formal analysis: BEB
Funding acquisition: BEB, SRJ
Investigation: BEB
Methodology: BEB, KLR, TRG, SRJ
Project administration: SRJ
Resources: TRG, SRJ
Supervision: TRG, SRJ
Validation: BEB
Visualization: BEB
Writing – original draft: BEB
Writing – review & editing: BEB, KLR, TRG, SRJ

Competing Interests

The authors declare there are no competing interests.

Funding Information

Government of Ontario: Ontario Graduate Scholarship
College of Biological Sciences (CBS): Graduate Student Research Assistantship Scholarshi
This work was funded in part by a Graduate Student Research Assistantship Scholarship from the College of Biological Sciences (CBS) and the Ontario Graduate Scholarship.

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