Converting a face-to-face neuroanatomy course-based undergraduate research experience (CURE) to an online environment: lessons learned from remote teaching

Abstract

Previously, we described a course-based undergraduate research experience (CURE) for first-year students that featured a unique approach to brain mapping in a model organism (rat). In response to the COVID-19 pandemic, we adapted this course for an online learning environment, emphasizing image analysis (identifying immunoreactive signal in an immunohistochemical stain, making neuroanatomical distinctions in a cytoarchitectural stain) and translation of image data to the brain atlas. Using a quasiexperimental mixed methods approach, we evaluated aspects of student engagement and perceived gains in student confidence with respect to the nature and process of science and student science identity development. Additionally, we examined the dynamics of mentorship and student connectedness experienced in the online-only context. We found that the majority of students reported positive affective outcomes for the course in domains such as project ownership and project engagement in addition to positive responses toward perceived mentorship received during the course. Unsurprisingly, students expressed frustration in not being able to freely communicate with members of the course in an organic face-to-face environment. Furthermore, we found that students encountered greater difficulty in mastering image software skills causing a delay in producing consistent-quality data maps. From our analysis of the course, we have identified both useful approaches and areas for course improvement in any future iterations of the online research course.

NEW & NOTEWORTHY Herein, we describe the process of converting a novel, face-to-face neuroanatomy course-based undergraduate research experience (CURE) to an online-only research setting. We document student affective and skill gains resultant from participating in this course and examine best practices for structuring online CUREs to maximize student learning and success.

INTRODUCTION

Course-based undergraduate research experiences (CUREs) represent environments wherein students have access to mentored research training while pursuing novel scientific discoveries, often with the intent of sharing their findings with the broader scientific community (1–3). While multiple factors contribute to diverse positive affective and learning outcomes reported in the literature, a portion of a CURE’s success in these dimensions can be attributed to engaging students in actively carrying out the processes of science, thus bringing relevance to content knowledge (4–7; see also, Ref. 8). In response to the COVID-19 pandemic, there has been increased interest in adapting these courses to accommodate safety guidelines (namely, low-density classes with activities that respect social distancing or that are converted to remote learning). It should be noted that, while the shift to online-only research courses represents a response to exigency, a remote learning format could represent a useful platform for training research faculty, students, or crowdsourced participants. Furthermore, an online CURE might provide innovative approaches to engaging online/correspondence students or might support intercampus collaborations that allow institutions to share and access unique resources, thereby extending student access to early research experiences. With this potential utility in mind, it is valuable to explore successful practices in online research mentoring and to identify the potential pitfalls instructors and curriculum designers should seek to address.

Broadly, when adapting CUREs to the online format, there are several direct challenges to the key pillars of collaboration, iteration, discovery, scientific practices, and broader relevance (1) (Table 1). Briefly, in face-to-face settings, CUREs emulate the activities and mentoring students would receive upon joining a faculty’s research laboratory. Access to discipline-specific tools and materials within a safe and controlled setting allows students to work with the fundamentals of science process, gain a visceral and intuitive understanding of how data are produced, and gain appreciation for the limitations and characteristics of the data being collected. Students have immediate input from the course research mentor and from fellow classmates. Furthermore, students engaged in face-to-face research laboratories have the advantage of shared dedicated time: in other words, students and their teammates share a single point of time that does not conflict with other courses, family obligations, or work obligations, thus allowing them to coordinate synchronous research efforts.

Table 1.

Overview of the approaches used in online BMC to address common online course challenges, as aligned to the five dimensions of CUREs

Face-to Face Practices	Online Course Challenges to Address	Mode of Addressing
Collaboration
Students work in teams in real time to achieve the research goals for the course.	Coordinating remote teams.	Creating student teams of four.
Feedback from the course mentor is immediate and often able to benefit multiple groups simultaneously.	Maintaining communication (student-student; student-teacher).	Proactive and frequent communication via platform tools.
	Providing opportunities for simultaneous effort.	Selecting a learning management platform that allows file sharing, screen and control sharing.
	Providing community building climate.	Modeling communication behaviors.
Iteration
Students review their records to troubleshoot procedures with the benefit of real-time input from mentors, classmates, and team members.	Creating a set of project goals and timelines.	Setting regular weekly deadlines for work turn-ins.
Students repeat protocols during a specified period to gain greater proficiency in science skills.	Enable instructor and classmate feedback.	Providing feedback and examples during synchronous class sessions.
Students have real-time access to a research mentor with the benefit of immediate feedback and guidance.	Foster troubleshooting.	Providing workshop sessions to students who may need extra time or reminders before work is due.
	Allow repetition to build proficiency in science skills, which can be carried out online during synchronous practice sessions or asynchronously by individuals and/or teams.
Discovery
Students discover content knowledge to understand or formulate a novel research question/project.	Maintaining active-learning pedagogy in lieu of lecture-focused content delivery.	Providing sets of tutorials for students to view in lieu of lectures during synchronous class time for content delivery.
Students collect data/make observations and contextualize their findings based on their accrued knowledge.	Ensuring that students can work to produce something novel.	Making use of data images that are generated in pursuit of a novel research question.
Scientific practices
Students learn the basics of notebook keeping, data collection, and responsible and ethical research conduct.	Controlling and maintaining records online.	Developing an online notebook with clearly defined fields for key documentation.
Laboratory facilities with appropriate safety engineering allow students to engage fully with relevant wet bench activities.	Identifying scientific practices that are suitable to online-only settings.	Focusing on analyzing digital data in lieu of generating at-home kits of physical materials or requiring a hybrid format of in-lab and remote learning attendance.
	Ensuring students have access to appropriate and safe tools.
Broader relevance
Students may collect data for the purpose of sharing at a campus-specific venue, regional or national conference, or contribute to a larger body of work for publication purposes, as all stages of the work have been supervised by a qualified research mentor.	Managing data (tracking, access, storage, version controls, consistent format).	Creating a shared file folder to manage student data and requiring file names that reflect new versions.
	Vetting data generated/QC.	Expert reviewing of student data for accuracy and completeness before final inclusion in any public report.
	Selecting appropriate venues to share potentially limited findings.	Assuring students can share findings and considerations with each other and lab mentors even if a conference poster is not developed.

We have outlined the aspects of the traditional brain mapping and connectomics (BMC) course that serve each of the five defining pillars for course-based undergraduate research experiences (CUREs) and aligned them to challenges we attempted to address in our online adaptation of the course.

In contrast, online research does not afford biology laboratory students a purpose-specific space featuring the necessary safety and risk management architecture, nor does it guarantee that students have protected time in which to carry out collaborative activities. Furthermore, while synchronous classes held as video conferences allow students to “meet” simultaneously and enjoy a sense of immediacy, this format features a more turn-based style of conversation that restricts the amount of attention and number of interactions a student can enjoy during the class meeting (9–15). In summary, the nature of activities in the online CURE must ensure student safety while providing students with a project that allows for discovery. The architecture of the course should provide students with opportunities to establish communities of practice, should promote student comprehension of the nature and process of science, and should support scientific rigor in student products to enable dissemination of findings (Table 1).

With these challenges outlined, we restructured our Brain Mapping and Connectomics (BMC) course (previously described in Ref. 16) for the online environment (Table 1). The restructuring process placed an emphasis on providing instructor accessibility and online student interactions, while attempting to balance the synchronous class time demands on a student population facing COVID-related work-life challenges.

Using both quantitative and qualitative approaches, we assessed student gains in science identity and skills development as well as gains in their affective outcomes. Additionally, we examined the students’ perceptions of the quality of mentorship received and the connectedness that they felt toward their classmates and the class instructors. Finally, we asked students to identify the challenges that they faced in conducting collaborative research in the online environment to identify areas of the course requiring further development. Here, we highlight useful practices and identify ongoing challenges to be addressed in future iterations of the curriculum.

Course Requirements and General Structure

This course was offered during the Fall 2020 semester as an online-only research stream. Pre-/corequisites for the course were kept consistent with the face-to-face version of the course described previously: enrollment in General Biology (the corresponding lecture course) and coenrollment in a research foundations course designed to develop basic science literacy and science inquiry practices (16). The original in-person course met for two 3-h sessions; however, in recognition of COVID-19-associated burdens (family care, work, access to shared internet resources, etc.), we elected to hold one mandatory-attendance 3-h session per week synchronously through the Microsoft Teams (MS Teams) platform (Microsoft Corporation, Redmond) and offered a second optional online workshop session (also 3 h in length) for student groups who wished to receive additional instructor feedback or assistance. Student teams of between three and four members were created through random assignment at the beginning of the semester and remained consistent throughout the course (please refer to appendix 1: course syllabus), as had similarly been the case in prior face-to-face iterations of the course (16).

In the course description found in the syllabus and in a presemester email, students were informed of course requirements to have Internet access as well as a computer, laptop, or tablet capable of supporting MS Teams, Adobe Illustrator, and Adobe Creative Cloud (Adobe Inc., San Jose, CA). Web cameras and microphones were not required but were recommended for student convenience, as were digitizing tablets or a stylus-type computer input in lieu of a mouse or trackpad. No other materials were required for this course. Here, it should be noted that the use of webcams and microphones was not made mandatory for the course for two major reasons: 1) respect for the students’ and students’ family’s right to privacy (17 and 18); and 2) recognition of technological throttle (limitations on internet bandwidth resources, as most students were attending classes from their family homes where siblings and parents might also be streaming classes and work meetings or device-related limitations on CPU/GPU processing capacities due to simultaneous use of MS Teams video meetings and Adobe Illustrator). While we acknowledge that a “no webcams/microphones required” policy might influence student learning and discussion, it should be noted that additional means of communication (MS Teams chat, shared documents, etc.) existed to foster student-student and student-faculty connections as well as to advance the pedagogical- and research-oriented goals of the course (see Course Implementation below). Previous studies (e.g., Ref. 17) have demonstrated that this combinatorial approach can be particularly effective at increasing communication and fostering equity in the classroom.

Course Goals, Learning Objectives, and Research Objectives

Course goals.

In addition to meeting the challenges outlined in Table 1, we wished to ensure that students were able to feel that they engaged in scientific research, gained a sense of what it is to be a researcher, and felt bolstered in their identity as a researcher through increased confidence in their ability to engage in scientific practices. To accomplish these goals, the instructors of this 14-wk CURE created a course architecture that emphasized real-time communication options, structured feedback, consistent deadlines, and student teamwork to ensure that the first-year students enrolled in the course did not feel disconnected from a learning community of peers and research mentors.

Student learning objectives.

After completing the course, students should be able to 1) recognize that the brain is a highly organized structure containing distinct functional regions that send information to and receive information from other functionally distinct regions; 2) identify key functions (feeding and satiety, emotional regulation, pain processing, etc.) of major brain regions; and 3) identify and delineate these distinct organized regions in images of histochemical preparations as defined by cytoarchitectural characteristics according to a reference atlas (19).

Research objectives.

Our research objectives for the semester were 1) to analyze images of coronal cross-sections of one rat brain prepared with a cytoarchitectural stain to identify and delineate the neuroanatomical structures of the amygdala and paraventricular nucleus of the thalamus (PVT) (as defined, in part, by neighboring structures in the gray and white matter of the brain) as depicted in the course reference atlas (19); 2) to identify choleratoxin B subunit-immunoreactive (CtB-ir) neurons indicative of retrograde transport from the region of the periaqueductal gray (PAG) in the aforementioned structures; 3) to combine information from cytoarchitectural boundaries and CtB-ir images to translate image data to an atlas model in a representative fashion; and 4) to identify broad patterns of neuron distribution within the student-selected regions of interest (please see Course Content Adjustment for further detail) putatively sending axonal extensions to the PAG.

Course Implementation

Course preparation: creating the data image bank.

One adult male Sprague-Dawley rat was singly housed in a humidity- and temperature-controlled vivarium with a 12-h light-dark cycle. At a weight of 401.0 g, the animal was stereotaxically injected at the coordinates anterior-posterior: −4.4 mm from bregma; medial-lateral −0.3 mm midsagittal sinus; and dorsal-ventral: −6.0 mm from brain surface with the retrograde tracer CtB in vehicle (0.25% in 0.1 M PB at pH 7.5). As is customary with independent CUREs (i.e., CUREs in which the research topic is based on a faculty member’s research interests and expertise), this injection site near the periaqueductal gray was selected in service of contributing data to a larger program of research directed by the on-campus faculty laboratory that serves as the “host” for this course. After a 30-day incubation period, the animal was humanely euthanized and preserved via transcardial perfusion in 4% buffered paraformaldehyde (PFA) and postfixed in 20% sucrose, 4% buffered PFA.

The brain was dissected and sectioned in the coronal plane at 30 µm, collected in four series in cryoprotectant, and stored at −20°C until processed. One series was selected for Nissl-body staining with thionine. An adjacent series was immunohistochemically processed for CtB-immunoreactivity using a nickel-enhanced diaminobenzidine chromogen (goat anti-CtB, AB 10013220, List Biological). Slide-mounted tissues were then imaged at 10× magnification using a Zeiss Axio Imager M.2 epifluorescence microscope (Carl Zeiss Microscopy, LLC, Thornwood, NY) driven by Neurolucida software (MBF Bioscience, Williston, VT). All animal, histochemical, and imaging procedures were conducted by experienced laboratory personnel (V.I.N. and K.N.) before the start of the semester. Working image files were provided to students at a lower resolution to reduce the computer processing burden, but full-resolution images for final checks were made available in a Files tab on the MS Teams platform dedicated to student products.

Course preparation: presemester student contact.

Before the start of classes, the instructors provided students with a video that introduced the major research goals of the course, course expectations (including the synchronous meeting structure of the course), the team-based nature of the research project (working in groups with 3–4 members through video conferencing software), workload expectations, grading policies, best practices in research, and a detailed description of the layout of the course site on MS Teams. The link for the video was included in a welcome email that provided a brief summary of the video contents and the course syllabus (see appendix 1).

Course preparation: generating a course tutorial bank.

The CURE designer (C.E.D.) created a series of course-specific tutorials to provide students with informational resources that were easily accessed from remote locations and that could be reviewed when needed. Topics included basic neuroanatomical terminology, features of the course brain atlas (19), basic histochemical concepts, neuron and neurotransmitter function, use of the relevant features of Adobe Illustrator, and brain mapping basics. Students were encouraged to review the videos before attending synchronous class sessions where the material would be discussed and techniques put into practice. Videos were created to 1) reduce the time required to introduce basic principles during synchronous class time and to optimize synchronous time for student questions, practice, and technique mastery; 2) to provide students with a free informational resource in lieu of expensive textbooks; and 3) to provide students with course-tailored information while adhering to institutional on-campus personnel restrictions in place in response to the COVID-19 pandemic. Due to institution-specific restrictions on filming the processing and use of animal tissue in research that existed during the inception of the course, creating in-house videos of tissue processing was not possible at the time that this course was deployed; therefore, those types of videos were not a part of the tutorial bank generated for the curriculum presented here.

Course preparation: structuring Microsoft Teams as a learning management platform.

Students were added to a MS Teams shell for the course and invited to join via email. Two main channels were created to act as student forums: a general channel for class-related discussions and announcement posts, and a second channel for informal socializing. Students were shown how to initiate video meetings for their own groups and encouraged to use the instant messaging feature to contact team members and instructors.

Additional sections of the management platform included the following:

• A “Files” tab populated with subfolders containing course-appropriate literature, brain atlas files, raw image files, and student work;

• A video library tab (provided through Microsoft Streams) with tutorials (described above) and class session recordings; and

• A OneNote notebook tab containing image provenance information (the processes used to generate the images for the class) and other resources to help students understand the purpose of their research activities.

Course preparation: preparing a data management protocol.

To encourage uniformity in products, students were provided with an Adobe Illustrator template to be used in creating their image analysis files and were instructed to save edited files under new version names before uploading them to the class folder. A standard naming convention for files was also provided. Additionally, in lieu of a standard approach to notebooks, students were given spreadsheets (see appendix 2: student data spreadsheet example) to fill out that provided a structured guide for recording observations. Feedback on assignments (atlas level assignments, parcellations, and, in some instances, identification of immunopositive neurons) was provided during synchronous class time, allowing instructors the chance to highlight common issues and to encourage collaborative input in revisions.

Scheduled class and workshop sessions.

Video conference meetings with mandatory attendance were scheduled and set to automatically populate student calendars, and reminder emails of class meeting times were sent out each week. The optional workshop sessions offered midweek were similarly scheduled through the MS Teams platform. Frequently, video recordings of class sessions that introduced novel content were made available through the Streams channel for the course. Regular Friday work turn-in reminders were sent manually the day before work was due rather than assigning items through the MS Teams platform.

Instructor access and communication.

In addition to on-camera presence in leading discussions, providing examples and feedback, and answering student questions and concerns during synchronous classes and workshops, both the graduate teaching assistant and the instructor of record for the course provided email information and highlighted the direct message function in MS Teams. Students were encouraged to contact an instructor if they had any questions or needed to schedule a separate video conference for themselves or for their group. Instructors maintained a rapid response policy for email (response within 24 h) and MS Teams messaging (response within 12 h of a message). Given the course enrollment (26 students), it should be noted that the course instructor-to-student ratio was 1:13.

Course content adjustment.

In our previous iterations of the BMC course, many of the first-semester activities were focused on the use of histological techniques to prepare tissue for microscopy and imaging (see Table 2 for a course comparison summary). Given the lack of access to proper and safe research spaces, the activities carried out in the first semester of this two-part course were not feasible in the online-only version. For this reason, activities of BMC online were aligned with the second-semester activities of the in-person course, as illustrated in Table 2.

Table 2.

Comparative overview of the in-person and online BMC CURE

In-Person BMC		BMC Online
Semester I	Semester II	Semester I
Activities
Neuroanatomy and atlas usage	Adobe Illustrator training	Adobe Illustrator training
Histology (mounting and Nissl stain)	Neuroanatomy and cytoarchitecture (parcellation)	Neuroanatomy and cytoarchitecture (parcellation)
Immunohistochemistry and microscopy	Signal identification	Signal identification
	Data mapping	Data mapping
Instructional conditions
Laboratory setting	Laboratory setting	Online setting
Lab computers with technical support	Lab computers with technical support	Students’ personal computers with limited technical support
All relevant software preinstalled	All relevant software pre-installed	Students were provided with subscriptions to relevant software
Meetings in person; 3 h a session; 2 sessions per week	Meetings in person; 3 h a session; 2 sessions per week	Meeting online for ∼1.5–2 h once per week (required) with a 3-h online workshop period (optional)

In comparing Brain Mapping and Connectomics (BMC) online and in-person versions, it is important to note that activities for Semester I do not align in scope and environment. Rather, the online course reflects the activities and research goals of Semester II students, wherein digital image analysis represents the bulk of research activities, lending itself well to the online environment. CURE, course-based undergraduate research experience.

In prior face-to-face semesters, students were able to carry out background research to select a region of the brain for study and formulate a research question, rationale, and protocol (receptors, neurotransmitters, or other important features to be identified via immunofluorescent labeling). However, due to a shift in COVID-19 policies, access to research spaces became highly controlled, necessitating responsive adaptation of the initial course syllabus and a reduction to examining and contextualizing data from images of immunohistochemical staining for the retrograde tracer choleratoxin B.

Consequently, students spent 3 wk investigating the functions associated with various brain regions and developing a hypothesis regarding: 1) which regions of the brain may be in communication with the periaqueductal gray (PAG) based on prior published observations; and 2) the distribution of neuron populations sending connections to the PAG (e.g., if students expected contralateral or ipsilateral connections to be more abundant, which regions of the brain would be more likely to communicate with the PAG given its known functions, if neurons sending projections to the PAG are evenly distributed throughout a region of interest or if populations exhibited a distinct clustering within a region of interest). While the nature of the project was largely observational, student teams were able to present an argument to the class to support their selected region of interest and their hypothesis during a synchronous video meeting. During this time, students in the course were called on to provide feedback to the presenting team (highlighting merits and flaws in rationale). The students then voted on which line of investigation to pursue and formalized the research question and region of interest for the semester.

METHODS

Student Population

Twenty-six students were enrolled in the online course, of which 15 students: 1) provided consent to use their survey data; and 2) also completed all surveys. Of these, the majority of respondents self-identified as female (93%) and Hispanic/Latinx (87%). While the female representation among respondents vastly outweighs male representation with respect to university demographics (∼53% female institutional enrollment), it should be noted that, for the total course enrollment, self-identifying females represented 81% of the class population. Additionally, the observed weighting in Hispanic/Latinx representation is closely aligned with the general university demography (∼83% Hispanic/Latinx).

Roughly 40% of respondents reported being first-generation college attendees. All but one student reported this course as being their first experience with research. Students were predominately in biology-related majors (87%), of which 20% were enrolled in the neuroscience major. Additionally, to determine students’ baseline familiarity with using social media tools to stay in touch with friends and family, students were asked to report on their frequency of social media use (Facebook, WhatsApp, etc.). All students reported making use of social media, of which 87% used social media at least once a day. Finally, when asked about familiarity with online learning management systems (LMSs), 100% of students were familiar with the use of Blackboard (Blackboard, Inc., Washington, DC), and 93% were familiar with the course LMS, MS Teams.

All participation was voluntary, and surveys were administered by noninstructor personnel in accordance with policies and procedures established by the university’s Institutional Review Board (IRB Approval No. 1636321). Unless otherwise indicated, all instruments were administered to participants at the end of the semester (postsemester).

Student Science Process Skills: Undergraduate Research Student Self-Assessment

At the conclusion of the BMC course, a modified version of the Undergraduate Research Student Self-Assessment (URSSA) (20) was administered to gauge students’ perceptions of gains in science process skills development, personal gains, gains in research skills development, and engagement. Student responses were reported on a five-point Likert-item scale (“1” = lowest or most negative rating; “5” = highest or most positive ranking). Scaling criteria were dependent on the dimension being evaluated, as follows: 1) thinking and working like a scientist, personal gains, and skills (no gains to high gains); and 2) attitudes and behaviors (not at all to extremely frequently).

Research Self-Efficacy

In addition to students’ self-perception of gains experienced, we complemented the URSSA with the Research Self-Efficacy (RSE) scale (21), a six-item inventory of “I can…” statements regarding students’ beliefs about their ability to engage in a diversity of general scientific practices and skills (theory development, science literacy, experimental design, etc.). This scale was administered at the end of the semester, and students were asked to provide agreement scores to statements on a Likert-item scale (“1” = strongly disagree; “5” = strongly agree).

Student Skills: Neuromapping Scoring Rubric

As previously reported, we developed a rubric for the course to aid instructors in quickly evaluating student image analysis (please see Appendix II in Ref. 16 for a full description of rubric implementation). Briefly, the original rubric addresses four major categories: 1) organization of file and layer names in Adobe Illustrator, which demonstrates that students have a grasp of the importance of creating annotated records with functional organization; 2) atlas proficiency, as demonstrated through identifying the correct atlas level and distortions due to plane of section; 3) neuroanatomical proficiency, wherein students demonstrate discernment of brain structures by correctly bounding and identifying structures in a cytoarchitectural stain; and 4) signal identification, wherein students demonstrate their ability to detect and distinguish immunoreactive features in the image. Because students were provided with templates and instructions in file naming in lieu of collectively generating a class standard, because they were unable to complete marking CtB-ir cells before the end of term, and because they were only responsible for labeling one hemisphere of the brain (thus negating the potential for a shift in axis and/or plane of section based on tissue preparation), we restricted the Neuromapping Scoring Rubric (NSR) evaluations to the first criterion of the Atlas Proficiency category, all criteria of the Anatomical Proficiency category, and one aspect of the System and Logic category (consistency of demarcation). Given that course products are intended for broader dissemination, accuracy and product consistency are a must. Work with >30% inaccuracy was assigned a score of “0” (meaning further iteration is needed). Work exceeding 70% accuracy was assigned a score of “1.” Student files were blinded and analyzed by two raters with expertise in biology education (J.T.O. and C.E.D.), achieving strong interrater reliability [kappa = 0.924; P < 0.001; 95% confidence interval (CI) (0.859, 0.989)]. All disputes were resolved through discussion between the coders until consensus was obtained.

Student Engagement: Video View Tracking

To determine how often students were availing themselves of existing video resources, we collected Microsoft Streams-provided view count data for each of the course tutorials and for each of the recorded class sessions. It should be noted that view tracking does not provide details as to the number of different individuals viewing the videos and, thus, all numbers expressed are subject to “view inflation” from one individual viewing the video multiple times for review purposes.

Student Engagement: Networking

The networking (NW) scale (22) was used to evaluate the extent to which students communicated about their course research with individuals outside of the course itself. Given the generally isolating experience cited in studies of online and correspondence courses (9, 12, 15, 23, 24), we were particularly interested to see if students were engaged enough with the activities and content of the course to talk about their research with friends and family members, and understood that students may or may not have the opportunity to discuss their research with students and professors outside their class or institution. Student responses were recorded using a five-point Likert-item scale (“1”= strongly disagree; “5” = strongly agree).

Student Identity: Science Community Values

We administered the Science Community Values (SCV) (21) at the end of the semester. This survey is designed to have students reflect on the extent to which their own scientific values are or are not like the hypothetical person described in each statement. It then asks respondents to rate how well these statements align with their own views of science in society (“1” = not at all like me; “2” = not like me; “3” = a little like me; “4” = somewhat like me; “5” = like me; “6” = very much like me).

Project Ownership Scale

We were especially concerned that students may not view the online research activities as “authentic” research but rather as “busy-work.” The Project Ownership Scale (POS)-Content (25) contains statements associated with student engagement and interest in their research project, autonomy, and recognition of the value of the knowledge resultant from their research. Participants’ level of agreement with each item statement is recorded using a five-point Likert-item scale (“1” = strongly disagree; “5” = strongly agree).

Students’ Perceptions of Course Environment: Course Factors Influencing Satisfaction and Connectedness, Challenges, and Suggested Improvements

To gain greater insight into where online-only research presented the greatest challenges to students, we provided a set of open-ended questions midway through the semester asking: 1) What has contributed most to your connectedness to or engagement with the course?; 2) What have you found most challenging about this semester?; and 3) Other than being in person, what one thing would you like to see changed that would improve your course engagement? Student responses were blinded and evaluated by two coders with expertise in biology education (J.T.O. and C.E.D.) using an inductive approach designed to elicit themes from the dataset (26). This process yielded strong interrater reliability (kappa = 0.954; P < 0.001; 95% CI [0.903, 1.000]), with all disputes resolved through discussion between the coders until consensus was achieved.

Students’ Perceptions of Course Environment: Mentorship Evaluation

Given the frequent issues students encounter in online learning environments with respect to connectedness and immediacy (9, 11, 13–15, 17, 23, 24), we included multiple modes of communication in the LMS architecture and made intentional decisions in “humanizing” research mentors and the process of research through sharing of personal experiences in research (including humorous anecdotes or lessons learned through mistakes) and using emojis in chat, when appropriate (27 and 28; see also Ref. 15). We wished to evaluate the efficacy of our efforts and identify aspects that could benefit from greater attention in future iterations of the CURE. To that end, we administered a brief, nine-item mentoring scale (29) at the end of the semester. Students’ indicated the extent to which they felt the instructor of record engaged in various mentoring behaviors via a Likert-item scale (“1” = not at all; “2” = to a small extent; “3” = to some extent; “4” = to a moderate extent; “5” = to a very large extent).

Statistical Analysis

Given the small sample size associated with this study, evidence for the face validity of all survey items was obtained both by reviewing the phrasing of statements in our earlier work on in-person iterations of BMC (16) as well as by soliciting feedback on the suitability and clarity of statements from students and faculty who were uninvolved with this research but who were familiar with CUREs. Descriptive and/or frequency statistics were tabulated for all survey items.

RESULTS

Student Skills and Affect

Perceptions of confidence in process and self-efficacy domains.

Overall, students reported experiencing gains in general skills development including “managing my time” (87% good/great gains), “working with computers” (87% good/great gains), and “understanding the relevance of research to my coursework” (100% good/great gains) (Fig. 1A). Interestingly, “defending an argument when asked research-related questions” scored slightly lower than other categories dealing with project understanding, suggesting that engaging students in greater degrees of challenge to articulate their reasoning should be considered in future iterations of the course. Greater variation in gains was likewise observed for the item “keeping detailed records of research-related tasks” (47% good/great gains), suggesting that our use of nontraditional spreadsheets in keeping information organized and categorized may not have been an effective practice for students. Encouragingly, students reported agreement to strong agreement with self-efficacy statements with relative consistency (Fig. 1B). Taken together, these data suggest that respondents experienced benefits in line with expectations for face-to-face versions of the course, with manageable exceptions.

Figure 1.

Student perceptions in skill gains. A: frequency data for the Undergraduate Research Student Self-Assessment (URSSA) as reported by participants using a Likert-item scale (1 = no gain; 5 = great gain). B: frequency of agreement scores with statements pertaining to research self-efficacy as measured via a Likert-item scale (1 = Strongly disagree; 5 = Strongly agree).

Student outcomes in research activities (NSR).

While analysis of student responses revealed perceived gains in research-related skills and self-efficacy, the overall degree to which students were able to achieve high-quality final products for the course was highly variable. In using the NSR to score student maps, we found that the majority of parcellations exhibited incomplete structure delineation within the regions of interest, incorrect or arbitrary bounding of the major regions and subregions, and incomplete labeling of structures. In contrast, students exhibited greater proficiency in their ability to discern cytoarchitectural differences among brain regions, correctly label dominant atlas levels, and make first-pass attempts at marking immunoreactive cells in image overlays (Fig. 2).

Figure 2.

Student functional gains in neuroanatomical mapping. A: a first iteration of student parcellations of the Nissl preparation for one tissue section using The Rat Brain Atlas as reference (19). B: the revised parcellation of the regions of interest and an image of immunohistochemically processed tissue series (set to 50% opacity) are shown here overlaying the Nissl-stained counterpart. CtB-immunoreactive cells have been annotated in this example (a step completed by few groups in this student cohort). C: average scores and standard deviations (SD) for final student work (12 images in total). Items from the original Neuromapping Scoring Rubric (NSR) that were not applicable for this cohort have been grayed-out.

Data mapping (vetted demarcation of immunopositive signal) and migration of that data from image files into the atlas could not be accomplished before the end of the semester. It should be noted that these final activities represent the data end-goal for class discussion and contextualization as a research poster and have historically been achieved by students enrolled in the face-to-face BMC course. It should further be noted that while the average scores for student products were low, certain individual groups showed above-average performance in their final product. These groups also displayed a strong cooperative group dynamic during synchronous class times and reported working together on parcellation efforts on their own rather than adopting a round-robin approach to assignments, suggesting an important role for peer collaboration in online environments, guiding critique and correction beyond that of the research mentor alone.

Student Engagement

Networking scale.

In examining the degree to which students reported discussing their research with noncourse contacts, at least half of the participants agreed or strongly agreed that they shared such information with friends and/or parents (Fig. 3A). These data suggest that students are engaged sufficiently with their project to share information with their inner social circles. We expected students to strongly disagree or disagree with statements indicating that they discussed research with noncourse/noninstitution professors and students, and were surprised to find moderate agreement within the average response for these categories. However, it should be noted that students enrolled in this course were concurrently enrolled in an interactive project-based course addressing science literacy and other research fundamental practices, which may account for the agreement observed in scholastic social circles.

Figure 3.

Student networking, community values, project ownership, and engagement with course video resources. A: student networking scores expressed as students’ agreement with “I have discussed my research with…” statements (target audience indicated on the y-axis). Likert-item scale used: 1 = Strongly disagree; 5 = Strongly agree. B: frequency of student agreement with science community values statements as measured via a 6-point Likert-item scale (1 = Not at all like me; 2 = Not like me; 3 = A little like me; 4 = Somewhat like me; 5 = Like me; 6 = Very much like me). C: student project ownership scores were captured using a Likert-item scale of agreement as in A in response to various tasks and attitudes (indicated on the y-axis). D: video resource viewing data provided by the MS Streams service is expressed here as raw view counts. Class recordings that correspond to a given tutorial topic are highlighted by corresponding shading patterns. Class sessions lacking a direct video recourse are depicted in white. “T” indicates a tutorial, whereas “R” indicates a classroom recording.

Science Community Values and Project Ownership

We were initially concerned that students participating in an online-only research course would fail to equate course activities with real-world research, including a failure to adopt personal research ideologies as encapsulated within the SCV scale (21). Students overwhelmingly self-identified with statements that described core attitudes researchers exhibit (see Fig. 3B), suggesting that either students entered this course having already adopted these views and retained them or that students were able to identify with the item statements having participated in course activities. Unfortunately, this snapshot does not allow us to judge gain or loss in strength of statement agreement due to course participation; however, we can at least state that science community values were not negatively influenced by participating in an online research course.

We were further interested in whether the loss of the wet-bench components of the course corresponded to low project ownership, as the hands-on component of CUREs and traditional laboratory courses alike are equated with high student engagement (1). We were very pleased, however, to observe high agreement with statements regarding project ownership (Fig. 3C). Most notably, students reported strong agreement with statements pertaining to interest in the project, finding the research project to be exciting, and gaining a sense of achievement. It was also encouraging to observe an overall agreement with autonomy-centric statements (advice seeking, overcoming challenges) and purposefulness (important to the scientific community, solving a real-world problem).

Video view tracking.

While video view tracking does not accurately represent the number of different individuals viewing a given video (i.e., one student may watch a video walkthrough several times when trying to follow along on a process), views do serve as a proxy for the utility of a given video. In the graph in Fig. 3D, videos are provided in the order in which they were posted. Note that while 14 class sessions were held, only 8 were selected for upload. These eight recordings contained novel content for students to review or addressed common points of struggle for students. Video tutorials that covered basic neuroscience concepts were viewed less frequently overall. Conversely, application-based walkthroughs received more hits. How to determine where to draw anatomical boundaries within the brain (“Parcellation”), how to determine if a cell is considered positive for immunoreactivity (“Cell Immunopositivity”), and how to use the software tools to denote immunoreactive cells (“Marking Immunoreactive Cells”) received the most attention. Views of class recordings were low overall, with class recordings 6 and 7 being the lowest. However, due to the manner in which view data are presented by Microsoft Streams, it is difficult to draw definitive inferences beyond suggesting that students did not feel compelled to review the provided recordings for class content. Future studies may benefit from a more rigorous tracking of viewing metrics and a targeted evaluation of factors that contribute to video utility.

Students’ Perceptions of the Course Environment and Mentorship

Open-ended responses on course factors influencing satisfaction and connectedness, challenges, and suggested improvements.

Students identified several course aspects that either positively contributed to or detracted from their course connectedness in a mid-semester survey (Fig. 4A). We were pleased to see that many students provided examples of features that positively contributed to course satisfaction, including mentorship (>50% of respondents), project ownership and course scaffolding (33% of respondents), and the collaborative nature of the course environment (25% of respondents). Unsurprisingly, the few negative reports of the course in this category were linked to its online nature. When prompted to provide the greatest challenge experienced in the course, most students made reference to impingement of natural communication; additionally, a quarter of respondents linked online challenges to technical difficulties including poor or unstable internet connections. Few students reported course content or time management as challenges (17% and 8% of respondents, respectively), although it is interesting to note that, in the suggested improvements category, half of respondents requested more clarification and examples compared to more frequent use of features that enhance interpersonal communication such as webcams and breakout rooms (17% in each category). Thus mentorship and team communication emerged as important course aspects bolstering student satisfaction.

Figure 4.

Student-perceived effects of the online environment. A: open-ended responses to three questions pertaining to what students viewed as the most impactful aspects of the online course or suggestions for future improvements. Percentages (rounded to the nearest whole %) indicate the number of students responding with that theme out of all total possible responses. Red font indicates themes associated with negative affective outcomes. B: Mentorship Scale scores were captured using a Likert-item scale regarding the extent to which stated actions were performed by the course instructor of record (1 = Not at all; 5 = To a very large extent).

Mentorship scale.

Given that mentorship for the course was highly featured among students’ open-ended responses, we were interested in determining what specific mentoring behaviors the course instructor of record was engaging in within the virtual classroom that were perceived to be most impactful by students. In responses to the Mentorship Scale (Fig. 4B), the strongest agreement with survey statements occurred in offering challenge and advancement (helping students to learn and grow in their research field) followed by task assistance, empathy, and interpersonal indices (qualities of availability and guidance). Of moderately lesser influence was the instructor’s contribution toward writing skills development and guiding peer interactions. Networking beyond the confines of the course scored lowest in agreement, and this, indeed, was not a strong focus of the course content or the course mentors.

DISCUSSION

Ensuring student engagement and providing a proper sense of immediacy and connection are challenging in online education. When dealing with the adaptation of a CURE-style course, there are additional considerations to address and criteria to be met (see Table 1). The course must provide students with a chance to iteratively collaborate in using scientific skills to address a novel research question with potential broader relevance to one or more external communities (1, 5, 6). As a primary research experience, the course must likewise introduce and maintain the core values of research, must support students in developing their competencies in the subject matter and in related skill sets, must encourage autonomy, and must engender legitimate participation.

Here, we have adapted the BMC course previously described by D’Arcy et al. (16) to an online-only format and described the impact of the course on both cognitive and noncognitive student outcomes. We must acknowledge several study limitations, however, which impact the generalizability of our findings. First and foremost, COVID-19 conditions represent an unusual set of circumstances that may or may not have had a direct impact on the scholastic focus of these first-year undergraduates (30 and 31). Additionally, our relatively small population of respondents (n = 15) in a class with a high proportional enrollment of self-identifying females does present challenges in extrapolating the impact of the CURE to other populations (e.g., male students). While not uncommon (see, for instance, Ref. 32), this is a limitation that warrants further investigation should the course be offered as an online option in the future.

Among our respondents, however, we observed perceived gains in confidence and skills proficiency. Indeed, this is reflected in improvement of student products over the course of the semester (exemplified in Fig. 2), even if the final products lacked polish by face-to-face standards—a factor we believe is mostly likely attributable to the challenges associated with needing to cooperatively generate maps while not being able to physically meet and conduct the research together on a single computer workstation. Importantly, however, as students received feedback and were able to refine their work, actual gains in skills and understanding were observed. Better performing groups appeared to have greater communication within the group and greater overall group rapport based on anecdotal observations from the course instructors. An in-depth analysis of in-class discussions to further analyze communication dynamics is currently underway. This preliminary observation, however, highlights the value of team structure and peer interactions in the learning process (12, 33–36) and also begs the question: “How do we, as instructors, further encourage team dynamics in online learning environments?” Despite lacking a face-to-face laboratory experience, students were able to appreciate their project and feel a sense of engagement. Thus, while the initial research goals of the semester were not accomplished by the majority of student teams, this online adaptation was still able to achieve many of the goals set forth for a CURE (1).

While research skills development was chief among our overarching pedagogical goals for the course, we wished to specifically address common factors of dissatisfaction cited by students enrolled in online or correspondence courses: loss of immediacy and loss of a sense of connection (9–15). With respect to immediacy, research mentors for the course (V.N. and C.E.D.) focused on proactive communication with students through emails, frequent feedback sessions in weekly video conference workshops, and rapid response to direct messages in MS Teams during normal business hours. When highlighting aspects of the CURE that supported course satisfaction as a function of connectedness, over half of the respondents included language expressing appreciation for the openness and availability of the research mentors (Fig. 4A). When further exploring the exact aspects students felt that the mentors offered, we discovered that providing challenge, supporting skill-building, and offering course- and interpersonal-related factors were cited most frequently. Empathy, sharing personal experiences, and being able to discuss anxieties and fears were perhaps especially valued by students given the uncertainty introduced by the COVID-19 pandemic (Fig. 4B) (27, 28, 37).

Notably, these mentor-student interactions were cited more often among respondents as having a significant influence on feeling connected to the course as compared to student-student interactions, although a quarter of students reported appreciating the team structure. At a glance, this highlights the value of using a learning management system that allows for file sharing, video conferencing, and screen control sharing tools to promote communication among student teams (10–12, 33, 38, 39). However, the intricacies of student engagement and communication styles within such a platform will be explored in further detail elsewhere. Taken together, our findings highlight the positive influence of the online BMC CURE on student course satisfaction and engagement rendered by providing students with attentive mentors, proactive communication, teams of peers, synchronous video conference elements, and regular detailed feedback and support on a consistent schedule (9, 11, 12, 23, 24, 27, 33–35).

Yet, coupled with these successes, we have found multiple points for improvement in the course design. First, it came to our attention from student feedback that the structure of the user interface for the learning management system requires revision. This was made evident when students reported wanting more instructional resources and examples. Here, it should be noted that student view counts for existing tutorial video resources (13 videos) averaged 11.92 viewings (SD 6.34), and student view counts of the 8 class recordings covering novel topics averaged 8.20 viewings (SD 3.52) (for a class of 26 students).

While frequent reminders, walkthroughs, and direct links were provided throughout the semester detailing where resources could be accessed, students largely did not access these resources. Furthermore, despite the degree to which students requested more examples and demonstrations, the walkthrough tutorials maintained low view counts, reinforcing the idea that dedicated tabs of folders within the platform were insufficient to promote student access. Thus, while there is value to providing students with more tutorials or live video demonstrations of the histology and imaging process used to produce data images (wet-bench-by-proxy), better site structure should enable students to locate existing task assignments, video resources, and course literature in a more at-a-glance method (10, 38, 40–43). Similarly, accountability for content review should be considered (online quizzes, minute papers that require students to reflect upon video content, or other interactive assignments for a portion of the course grade).

Second, given that online education is frequently assumed to allow a certain freedom of scheduling, coordination of group work outside of class meetings cannot be taken for granted (9). As such, in lieu of randomly assigning students to groups, we suggest administering a scheduling poll to students and to assign groups based on common time availability. Additionally, managing remote group dynamics through the use of synchronous breakout rooms would provide students with a guaranteed time during which all team members could contribute to the project, provide instructors with a means to monitor progress and moderate work-sharing habits within the group, and afford greater real-time execution of complex computer tasks with the benefit of immediate instructor intervention/mentoring (12, 23, 33, 35, 40).

Furthermore, the NSR evaluation illustrates that while students were able to grasp certain aspects of differences in cytoarchitecture unique to given structures in the regions of interest, they did not grasp some of the more nuanced aspects of parcellation. These skills have benefited from on-site immediate feedback in the traditional classroom setting. Thus, we reemphasize that use of synchronous session breakout rooms for students to conduct real-time work punctuated by mentor feedback (in lieu of a weekly task to be accomplished with delayed feedback) should strongly be considered in future course iterations.

Despite the flaws identified in the course architecture (e.g., the online nature of the course, poor leveraging of breakout rooms in synchronous sessions, LMS navigability), we still observed many of the same positive affective student outcomes associated with face-to-face CUREs. The course structure benefited from synchronous meetings and from regular interaction with and feedback from research mentors, despite needing optimization to offer more opportunities for group engagement in real time. Furthermore, students felt they experienced skill gains in research and project understanding. Finally, encouraging, proactive, and accessible communication from course mentors (as described earlier in Course Implementation and results) provided respondents with positive mentorship experiences. As we move forward, being able to leverage those data to better understand what students value in an online research course has provided us with a set of best practices that we may use when constructing future online CUREs, research collaborations, and crowd-training efforts.

DATA AVAILABILITY

Data will be made available upon reasonable request.

GRANTS

The Brain Mapping and Connectomics course was created under the UTEP PERSIST (Program to Educate and Retain Students in STEM Tracks) program funded by Howard Hughes Medical Institute Grant 52008125. This course was also supported in part through National Institute of General Medical Sciences (NIGMS) Grants GM109817, and GM127251 and NIGMS Awards RL5GM118969, TL4GM118971, and UL1GM118970.

DISCLOSURES

No conflicts of interest, financial or otherwise, are declared by the authors.

AUTHOR CONTRIBUTIONS

C.E.D., V.N., and J.T.O. conceived and designed research; C.E.D. and J.T.O. performed experiments; C.E.D., L.L., D.N., and J.T.O. analyzed data; C.E.D. and J.T.O. interpreted results of experiments; C.E.D. prepared figures; C.E.D. and J.T.O. drafted manuscript; C.E.D., L.L., D.N., and J.T.O. edited and revised manuscript; C.E.D., L.L., V.N., D.N., and J.T.O. approved final version of manuscript.

APPENDIX 1: COURSE SYLLABUS

The BMC semester calendar is shown in Table A1.

Table A1.

Brain Mapping and Connectomics Semester Calendar (subject to adjustment*)

Week	Synchronous Class Topic	Activities	Assignments	Tutorials
1	Teams navigating; general brain structures, anatomical directions and terminology; PAG specifics and questions for discussion	Intro and group formation, syllabus overview, contract, setting expectations for lab notebooks and why it is important, setting expectations for team management; information about the brain, nerves, and PAG	Sign and turn in contract via Blackboard. Assignment given in Tutorial Organization of the Brain!!! Prepare an overview of brain structures functions, key neurotransmitters, PAG specifics	Neuroanatomy Crash Course (NCC) Parts 1, 2, 3, 4: Terms, Organization of the Brain, Nerves
2	Setting up the foundations of research; introduce the atlas and review terminology	Hear student responses from the tutorial questions; Introduce Entrez PubMed use in finding literature (reviews and research); set up searches for a group presentation about where they want to go in the brain; flip through the atlas to find the extent of their structure	Regions assignment: prepare a defense with your team on what regions of the brain are of particular interest to you. Be sure to include: the function of the structure, any neurotransmitter information you come across, and the atlas levels that correspond to that region of the brain	NCC Part 4 & 5: Neurotransmitters; Gains in Brains are Mainly in the Stains (Cytoarchitecture and Chemoarchitecture)
3	Defending the foundations and structuring research; introduce tract tracing concepts; start introducing Inkscape software	Hear student group presentations (informal) and have a class vote on how we want to proceed; design the approach to data analysis	Review the Inkscape SVG tutorials in getting set up and creating new files from templates, file naming conventions, and storage; follow tutorial instructions to create a cartoon panel; be sure to create an entry in the lab notebook as per protocol and upload your masterpiece for evaluation	Swanson Rat Atlas Features and Use (includes how we prepare brain tissue for analysis, basic concepts in determining level and plane)
4	Introduction to parcellation; how we section, plane of section, and atlas level determination	Share animal information with the group from KN's notebook; introduce the concept of preservation of sample metadata when collaborating; have groups enter the information in their notebooks; include the image files that have been assigned to them; have groups set up a new file in AI (note taker records all actions in the lab notebook) and place their Nissls from the group folder into the new file; introduce teams to the parcellation data sheet	Continue working on setting up the files and establishing the workflow and duties within your research team to handle notetaking, atlas level determinations, and plane of section determinations	AI Files and File Management: creation, templates, naming, sharing, linking and embedding; AI Files Are Like an Onion or a Parfait: Guide to layers; Tools of the Trade: Finding and using the most commonly needed tools in Inkscape; Text Savvy: Controlling your text scale in AI
5	Introduction to Parcellation: Insane for the Brain Stain!	Open the floor for a discussion on animal use; review the turned-in products of the teams and open up the forum for discussion of boundaries and planes; teams take notes on feedback; external literature may be added to the discussion	Continue working on note-taking, atlas level determinations, and plane of section determinations; review notes on the technique and purpose of tracing	Guide to Parcellations: It's all in how you look at it
6	Getting Down to Data: Mapping the Injection Site	Student-led review in-class on tracing techniques; introduction to the next set of files for mapping	Injection site mapping for the assigned files in the folder	Making Tracks and Tracing Tracts: Injection site mapping and approaches in AI
7	Injection Mapping Part Deux	Refine previous work; comparisons of group style and approach; discussion on data unification strategies and the topic of variance; new samples may be available to map; start talking about the antibody list	Injection site mapping for the assigned files in the folder/addressing instructor feedback of the first-pass; talk over antibody list with your teammates to talk about potential future research projects
8	Getting Down to Data: Mapping the Cells of Origin	Progress check-in and evaluation of the lab members on attainable goals and end-product expectations; recap of project concept; general discussion of where we are heading and why; discuss the nature of microscopy vs. imaging and consider the responsibility(ies) of the researcher when collecting and curating data	CTB+ cell mapping for the assigned files in the folder	Calling a Cell a Cell; Cell mapping approaches in AI; Making Connections in your Brain about Connections in your Brain: Building a concept diagram
9	Mapping Cells of Origin Part Deux	Refine previous work; comparisons of group style and approach; discussion on data unification strategies and the topic of variance; new samples may be available to map	CTB+ cell mapping for the assigned files in the folder/addressing instructor feedback of the first-pass
10	Transferring Cells to the Model	Discuss the implications of transforming data, the nature of models vs. photographic fidelity, and best practices; discuss the different relationships to consider when transferring data	Transfer your cells to the atlas making sure that the relationships are respected	Transferring Cells to the Map
11	Transferring Cells to the Model Part Deux	Examine patterns of data together as a class to begin to link the work being done by each research team	Refine previous work and receive new samples
12	Counting Cells and Making Meaning	Review the data spreadsheet use and begin discussions on counts in tables vs. data on maps or from images	Provide counts for the files completed to date according to the data sheet instructions	Counting Cells in AI
13	Assembling the Story	A time to review abstract content and construction, the general approaches to displaying and organizing data including some aspects of graphic art and design; establish a lab poster artboard and determine the images, data, and flow of the poster	Prepare individual abstracts to share in class with the team for critique and unification; as a team, prepare image sets in AI on a posterboard	Building a Concrete Abstract; Considerations in Information Design and Presentation
14	Where do we go from here?	Discussion with the whole lab on where we have been in our journey and where we need to go next; we start thinking about the proposal: With the tissue remaining, what questions could we ask about the PAG and its connecting structures? Do these questions bring something new to the table? How would we set up that experiment?	As a team, prepare a brief proposed research plan (can be a diagram with a written description/figure legend, can be a spreadsheet, can be an outline) that summarizes 1) What we know from the literature and our data, 2) What we couldn't find from the literature that makes a compelling question, 3) Proposes what we could do with our current resources to address that question (design an experiment). Include citations at each appropriate point to provide proper credit to the authors (superscript the number corresponding to the reference in the reference page) and include a reference page with numbered references at the end. The lab PI will review these proposals and select one to adapt to the spring course!

*You might notice that our calendar of events has some room for adjustment. We recognize that science is a process and you are learning the ropes. Product evaluation may result in corrections and feedback from the research mentor that will require you to go back and make corrections. That’s why each step is evaluated as we go along. We learn best from feedback and the chance to make something better. While we set a goal, we will reach our destination when we reach it. Our lab is about the journey!

Brain Mapping and Connectomics Online Syllabus

Research Mentor Contact Information

Instructor email: cebond@utep.edu

or

Post to Teams General or send a chat message out to us

Scheduled Lab Meeting Hours

Mondays 2:30-5:20 pm

Scheduled Laboratory Consultation Hours

Wednesdays 2:30-5:20 pm

Course Goals

The goals of this course are:

1. To generate real-world research that is prepared for conference presentations and/or published in a peer-reviewed journal in the form of neuroanatomical maps;

2. To mentor apprentice researchers (you) in the processes of scientific research, data analysis, science communication, and the research culture.

This makes the Brain Mapping laboratory unique – you will not just learn a variety of research techniques, and you will not just mimic real research. You will participate in an actual project that provides something new to share with the scientific community. Along the way, you will pick up information about histological techniques, the workings of the brain, and neuroanatomical research approaches that are being developed and improved even as we work with these tools! You are not just students, but research apprentices. You will expand your critical thinking skills, be exposed to professional science writing, and be asked to talk about or write about your work and the topics that relate to it.

Project Goals

We are examining connections in the brain using male Sprague Dawley rats as a model organism. Specifically, we will be investigating and documenting neurons in various locations in the brain (gray matter regions) that send communications to a region known as the Periaqueductal Gray (PAG).

• The project findings will be mapped to a reference atlas (the Swanson Rat Atlas 4^th Ed., 2014, which is an atlas of the adult male rat brain), so that they will be easy for other investigators to use and to integrate with their own data.

• These maps will be prepared for presentation as a scientific poster including written content such as figure legends, the poster abstract, major findings/summary, and references.

The activities of this semester represent the first step in an investigative chain. Because different neurons express different neurotransmitters, each of which represents a unique function in the brain, the next steps will be to determine:

1. Which neurotransmitters we are interested in selecting to investigate, and

2. Which areas of the brain that communicate with the PAG do we wish to examine at a deeper level.

Thus, you will have a say in what that course of investigation will look like for next semester, the data you analyze this semester will provide that foundation, and you will have the ability to work with your research colleagues in forming a brief research proposal that will be presented to your research mentor.

Because there are so many different neurotransmitters expressed in the brain, and so many regions that may be communicating with the PAG, this is a long-term project with many possible future paths of investigation. But even among these first few steps, we can use this data to build a presentation or paper to share with the professional science world.

General Expectations

In order to achieve the primary course goals, you must:

• Be prepared to coordinate and communicate with your team and your research mentor;

• Be willing to invest time working on the project;

• Be diligent about documenting your process in evaluating the data so that a record is preserved for future collaborators who will build on this work

• Be invested in producing high-quality work that meets the stringent standards of the scientific journal or conference through which this project will ultimately be shared.

Data Policy Expectations

Protection of data: Because you will be conducting actual research, the information you generate in this laboratory is the intellectual property of [Institution]. The research mentor must have a copy of your most recent data files and notebook/data spreadsheet entries. If questions arise among the scientific community concerning the rationale that you used in representing your data, your laboratory notebooks/data spreadsheet entries will be referenced. Your laboratory notebook is considered a legal document. This is serious business. If these things are not kept up-to-date, the data evaluations become unusable and the project success as well as your authorship is placed in jeopardy.

Furthermore, as we are working on novel data and have used animal tissue to produce that data, we must avoid sharing the work on social media platforms or any meeting platforms outside of the secure [Institution] systems (MS Teams and Blackboard). This is to keep the data from being used by other laboratories (avoiding getting “scooped”), to ensure that the context of our data travels with the presentation of our data, and to ensure the safety of our students and researchers here at [Institution].

Required items: Computer/tablet with working sound output (speakers and/or headphone jack) capable of running SVG vector software (Inkscape or Adobe Illustrator).

Nice-to-haves (but not essential!): A stylus and tablet for some of the mapping work, though all of the mapping work can be accomplished with a standard computer mouse or touchpad. A computer microphone (built-ins are fine), a set of headphones/earbuds (to reduce feedback when the mic is on for discussions).

Grading Policy and Work Expectations

This is a research laboratory, and you have signed on to be researchers. As this course represents your transition from being a student to being a professional, the policies for grading are modeled after the real working world and employee reviews, including:

• Evaluation of your participation in the full-class lab meeting sessions,

• Evaluation of workload sharing with team members,

• Review of your work and documentation for quality and maintenance,

• Assessment of how well deadlines are met so that the research team may continue to progress toward our end-of-semester goals.*

As in the workplace, you may be assigned readings to help get you up to speed, and you may have to present information either about your progress, the project content as a whole, or other relevant topics. These will largely be a spontaneous, “Please share with us,” format that requires that you are able to speak knowledgeably about the topic at hand, or at least be able to identify what parts are still unclear to you. Formal PowerPoint-style presentations will very rarely be required, but if you feel this is the best way to present your information, you are more than welcome to create one and share. :)

There will be an end goal of preparing a brief proposal from your teams for where this research will go next semester. If you choose to stay with us for [course catalogue number], you will be working with a project that you or your fellow laboratory mates have proposed! More details will be provided throughout the semester.

“Grading”: Job Evaluation scales are typically 5 = exemplary/shows significant improvement, 4 = good/shows improvement, 3 = Average/maintaining, 2 = requires improvement, 1 = requires significant improvement. We will provide updates on your performance throughout the semester each month. You can request an evaluation at any time if you want to know where you stand before then, but if it is brought to our attention that you are not documenting your process, are not putting in the work, are not communicating with your teammates or mentors, are not showing up to laboratory meeting sessions, or are regularly not prepared to engage in discussion in laboratory meeting, you will be asked to meet one-on-one with your mentor for feedback and suggestions on how to improve your standing in the course. If you don’t show improvement in performance after that meeting, we may recommend you take the option to withdraw from the course if it is before [date] (this is the last day you can withdraw from the course with a “W” on your record in lieu of an “F” for the course).

TLDR—Make your best effort, communicate if something is going wonky, be a team player, don’t be unfair to your teammates.

If you are doing your job well, and are a team contributor, your GPA for the course will reflect this with an “A.” If you do not show improvement in poor work behaviors after a session with your supervisor, your grade will reflect this.

Academic dishonesty: In accordance with the policies of [Institution], academic dishonesty is considered wholly intolerable. Academic dishonesty is essentially any form of cheating. In the laboratory, this includes research dishonesty. Research dishonesty is any kind of falsification of data, creation of data that isn’t there, or even not providing a good record of what you did, how you did it, and why you did it. Students found to commit academic dishonesty will be disciplined following [Institution] established procedures, which you can read about here: [university link].

Plagiarism: Plagiarism is a form of academic dishonesty and will not be tolerated whatsoever. If any part of an assignment submitted by a student is plagiarized, the entire assignment will be considered plagiarized and will count as a zero (0). Particularly, flagrant and deliberate plagiarizers will be referred to the Dean of Students, in accordance with [institution] policies on academic dishonesty.

ADA accessibility: Students with disabilities who require accommodations must contact the Center for Accommodations and Support Services (CASS) as soon as possible [CASS contact information].

Community Goals

Remote learning is always a challenge, especially when social distancing is needed to keep us and our loved ones safe. We will be using a team management software that will enable you to start up video calls and share screens with one another so that you can work together in your groups even though you are working apart. This software also enables you to post to a general forum with the option to discuss new channels for different topics with your research team mentors, and enables you to chat privately with groups you create or individuals (including your research mentors). While we can’t currently enjoy each other’s company in the same laboratory space, we are doing everything we can to support the feeling of being a research family and share the enthusiasm this course has enjoyed in years past. Thanks for being a member of this team and working with us to make this a warm and rewarding experience for everyone!

APPENDIX 2: STUDENT DATA SPREADSHEET EXAMPLE

An example of the student data spreadsheet is shown in Table A2 with the following instructions:

Table A2.

Student data spreadsheet example

Animal #

Nissl File Name

AI File Name

#Revision

Parcellator(s) Initials & Date

Atlas Level(s) Represented

Rationale for Level Assignment (Key Landmarks)

Structure(s) Parcellated

Observations on Cell Characteristics (Cytoarchitecture) and Boundaries

Instructor Feedback

“This data sheet (Table A2) should be filled out while you are parcellating/having team discussions about atlas and boundary assignment. It may be helpful to work in teams (at least one notetaker and one parcellator sharing the AI application in MS Teams to have debates with and to share the workload is highly recommended). Note: not every field will need to be filled out each time. Rows 1–3 will only need to be filled out once. Rows 6–9 may require revisions based on instructor feedback. You are encouraged to discuss feedback with your instructor(s), as we are all humans in pursuit of well-debated knowledge. Don't be afraid to contest feedback, but do provide rationale and be open to discussion. Final versions will be highlighted in green by your instructor indicating that no further revisions are needed.”