Introductory Undergraduate Course Research Articles

Creating an Assignment to Incorporate Antiracist Pedagogy Into an Undergraduate Introductory Nursing Course.

Antiracist pedagogy was incorporated into an undergraduate introductory nursing course using National League for Nursing diversity and inclusion initiatives and academic nurse educator competencies as a framework. This article describes the reflective process and steps taken to select Taylor's memoir, Reminiscences of My Life in Camp, as a required text for an introductory nursing course. By incorporating antiracism into an introductory nursing course, educators can assist novice nursing students from diverse groups to envision themselves as nurses, role model allyship for White students, and create a more inclusive teaching environment.

Fink’s Integrated Course Design and Taxonomy: The Impact of Their Use in an Undergraduate Introductory Course on Bioinformatics

Fink’s Integrated Course Design and Taxonomy: The Impact of Their Use in an Undergraduate Introductory Course on Bioinformatics

Students got mail: Do students read semi-tailored emails and what is the impact?

This paper examines the effectiveness of providing personalised email feedback via an automated email application in a large undergraduate introductory accounting course. Over 1,200 students received feedback via emails sent weekly, semi-tailored to each student based on their results in online self-test learning quizzes. We first found that students read the majority of emails distributed. Second, through tracking, using regression analysis, we found that reading emails is related to significantly higher final examination performance in some cases. However, this is moderated by factors relating to diversity in a large cohort exceeding 1,000 students. The results indicate that feedback needs to be readily actionable and aligned with assessed learning outcomes to realise significant impacts on exam performance. This study is relevant to educators who teach large and diverse cohorts and need time-efficient solutions to tailor the learning experience to each student.   Implications for practice or policy: Undergraduate students read the majority of weekly emails distributed, indicating emails can be used as an instructor communication device. Emails should specifically encourage activity completion aligning with learning objectives to improve grades. Students who achieve lower grades in tertiary studies, from English-speaking backgrounds and medium to high socio-economic status, high performers at high school and younger students aged 20 or less are positively impacted. Therefore, emails should be used by instructors teaching cohorts with these characteristics.

Viewing tailored nudges is correlated with improved mastery‐based assessment scores

AbstractMastery‐based assignments typically provide students with multiple opportunities to improve their performance, but getting students to take advantage of these opportunities is difficult. We report on the implementation of a two‐part series of nudges designed to improve students' engagement with and performance on mastery‐based assignments in high‐enrollment, introductory undergraduate courses. Students received one or two email‐based nudges for each assignment, providing both decision information and decision assistance. Delivered via email by a digital coaching system that provides tailored support to students, we evaluated the effectiveness of viewing versus not viewing these personalized nudges across introductory courses in mathematics, computer science and engineering over five terms at our large, research‐intensive university. We used multilevel modelling with a sample of 30,693 assignment scores nested within 79 assignments and 5349 undergraduate students to explore the relationship between students' viewing the nudges and their scores while controlling for performance in other courses and students' baseline proclivities to read email from the coaching system. We find that viewing versus not viewing nudges is significantly related to improved outcomes. Viewing the first of the two‐part nudge series is associated with a 3% increase in scores on average. Importantly, we found a significant interaction with prior academic performance such that students with the lowest average academic performance across all courses are predicted to benefit the most—up to 9%—from nudging. Positive impacts are observed in most courses where nudges were implemented and are found to be most impactful for later versus earlier assignments within a term. We discuss the implications of these results for supporting students' decision‐making within mastery‐based assignment schemes and suggest future research for tailored nudges to support student success. Practitioner notesWhat is already known about this topic Nudges are known to be broadly effective, but heterogeneity is observed especially in education where the research base is relatively limited. Mastery‐based grading is an alternative approach to grading that, among other features, emphasizes learning through an explicit feedback cycle of struggle and revision without penalty. What this paper adds This study assesses the effectiveness of personalized nudges in the context of mastery‐based grading in undergraduate STEM courses. We examined the efficacy of viewing versus not viewing nudges in the real learning settings of three STEM courses enrolling more than 5000 students. We found the nudges to be effective overall, correlated with improvements of approximately 3% in students' assignment scores and most impactful for students with the lowest average academic performance. Implications for practice and/or policy Nudging by email or text message has a low overhead cost and yet may provide materially significant gains in students' assessment scores. Nudges can be effectively targeted to specific subsets of students and tailored based on students' prior and concurrent learning analytics data.

Evolution of an introductory undergraduate biology course through collaborative action research

Over the past few decades, we have witnessed an increasing emphasis on the significance of restructuring and revolutionizing undergraduate science education in achieving the goal of preparing a scientifically literate population and safeguarding our democracy and the future of STEM workforce. This paper reports on a collaborative action research conducted to reform and modify an introductory undergraduate biology course taught by the third author with professional support and feedback provided by the other authors. The findings will be discussed in the form of a case study focusing on the initial features of the course, continual feedback and professional growth, modifications to the course, and future plans for further revising the course.

Integrating Digital Editions and Methods for Text Editing and Analysis in Undergraduate Literary Studies

This article evaluates the integration of digital editions, computational text analysis and digital scholarly editing in the context of an introductory undergraduate course on Italian literature and digital humanities taught at a US university. It offers specific examples of employing the apparatus of several digital platforms dedicated to the study of foundational authors in the Italian literary tradition (Dante, Petrarch, Boccaccio and Leopardi), and of gaining familiarity with a suite of digital tools for text analysis and editing, namely Voyant Tools, Recogito, Oxygen, Gephi, Transkribus Lite and OpenRefine. The discussion of digital project interfaces examines the student user experience of different design approaches, while the illustrations of tool exercises explore how these could support the close attention to a text and facilitate the navigation between its micro and macro frameworks of interpretation. The article furthermore suggests that digital text analysis could reinforce student appreciation of the signifying value of textual form and genre, and that the pedagogical method of digital text editing creates opportunities for situated learning. In conclusion, it argues that the academic work of students at the undergraduate level could be harnessed by the scaffolded methods of faculty-led digital research projects and contribute to the creation of public knowledge.

Proposing and testing a model relating students’ graph selection and graph reasoning for dynamic situations

Using a mixed methods approach, we explore a relationship between students’ graph reasoning and graph selection via a fully online assessment. Our population includes 673 students enrolled in college algebra, an introductory undergraduate mathematics course, across four U.S. postsecondary institutions. The assessment is accessible on computers, tablets, and mobile phones. There are six items; for each, students are to view a video animation of a dynamic situation (e.g., a toy car moving along a square track), declare their understanding of the situation, select a Cartesian graph to represent a relationship between given attributes in the situation, and enter text to explain their graph choice. To theorize students’ graph reasoning, we draw on Thompson’s theory of quantitative reasoning, which explains students’ conceptions of attributes as being possible to measure. To code students’ written responses, we appeal to Johnson and colleagues’ graph reasoning framework, which distinguishes students’ quantitative reasoning about one or more attributes capable of varying (Covariation, Variation) from students’ reasoning about observable elements in a situation (Motion, Iconic). Quantitizing those qualitative codes, we examine connections between the latent variables of students’ graph reasoning and graph selection. Using structural equation modeling, we report a significant finding: Students’ graph reasoning explains 40% of the variance in their graph selection (standardized regression weight is 0.64, p < 0.001). Furthermore, our results demonstrate that students’ quantitative forms of graph reasoning (i.e., variational and covariational reasoning) influence the accuracy of their graph selection.

QuVis simulations in Czech - translation and utilization in pre-service physics teacher course

The collection of QuVis simulations is based on research on frequent student difficulties, and their design and effectiveness have been also verified. The concept of these simulations fits very well into our undergraduate Introductory Course of Quantum Physics for pre-service physics teachers. However, due to the simulations being in English, we recognized the language barrier as an obstacle for some students when working independently with them. Moreover, we believe that a solid grasp of Czech terminology is important for future teachers. These reasons led us to translate 20 simulations into Czech. To further enhance the collection, we are developing thematic worksheets that feature tasks using the selected simulations alongside tasks that are solved without their use. Up to now, we have published five worksheets focusing on measurement in quantum physics.

An Instructional Innovation That Embeds Group Learning in Case Teaching: The Table Case Method

Although combining case study teaching with group learning is a popular approach for teaching business courses, pedagogical challenges arise, particularly in undergraduate classes. To address these challenges, we developed an instructional innovation called the Team- Based Learning and Evaluation (TaBLE) Case Method, which increased student engagement and deepened learning in an undergraduate introductory management course. The TaBLE Case Method is built upon specific principles of team-based learning, and comprises phases that meld together individual preparation and group participation before, during and after class. Our evaluation of the TaBLE Case Method highlights how it enhances group learning by: increasing student motivation to prepare, attend and engage; creating individual accountability for group goals; fostering critical thinking and creative debate; and making theory-practice links more visible. We also discuss the method’s “shadowsides” and limitations, and provide guidance on how the method can be adapted for a variety of class sizes and delivery modes.

The Frayer Model as Analysis of Instruction and Student Knowledge in Undergraduate Astronomy

The American public’s factual knowledge about science has remained relatively unchanged over the past two decades. Research on scientific literacy connects to science education, interactive instruction techniques, and how introductory undergraduate science courses are many students’ last formal exposure to science. This highlights a need for research on how these courses can contribute toward a scientifically-literate citizenry. This study qualitatively analyzes how instruction in an introductory undergraduate astronomy course informs students on an astronomy concept, specifically blackbody radiation. A case study method of thematic analysis was employed by administering a pre- and post-lesson Frayer Model to students in an ASTR 1010 section and recording the professor’s lecture. Thematic analysis was conducted on all Frayer Models and the lecture transcript. Three key themes (refined understanding, blackbody spectrum, and ideal physical body) emerged, summarizing how students’ knowledge changed following instruction. The results section contextualizes these themes within how the concepts were taught. Blackbody radiation was entirely foreign to most students. Students utilized a few keywords, such as “perfect absorber,” to describe blackbodies. Their visual comprehension improved, for they accurately drew and labeled blackbody spectra. This study is novel in using the Frayer Model as an assessment tool in astronomy education research. The findings contextualize scientific literacy and nuance our understanding of how students conceptualize lecture-based instruction. Educators can interpret the results when considering how to teach blackbody radiation. Implications are made to a growing body of knowledge on language in astronomy education.

An interactive 3D model of thermohaline circulation to support learning in undergraduate introductory oceanography courses

Thermohaline circulation is a foundational concept in introductory and advanced undergraduate oceanography courses which describes the density-driven flow of water throughout the world’s oceans. This concept is commonly taught using two-dimensional (2D) diagrams and graphics. However, students often struggle with the three-dimensional (3D) patterns and connections associated with thermohaline circulation. To remedy this, we sought to present thermohaline circulation in three dimensions to enable students to apply their knowledge and work with physical models. We constructed an interactive physical model of thermohaline circulation which included 3D printed continents and Arduino-controlled LED strips colored to represent global temperature and salinity patterns. We implemented the model as a teaching tool in a large undergraduate introductory oceanography course during the module covering thermohaline circulation. In discussion sections, students utilized the model to observe patterns, match depth profiles of real data to different geographic locations, and apply their knowledge to draw their own depth profiles using the model. After completing the in-class assignment, we assessed whether the model helped students understand and apply key concepts from lecture using both student worksheet responses and self-assessment surveys. Student scores increased significantly after using the model, and self-assessment data suggested students enjoyed using the model as well. The model is broadly applicable to a variety of settings, including other undergraduate courses, K-12 outreach, and public engagement to support oceanographic learning across a range of levels.

Human Resource Management Reimagined: A New Perspective on HR Courses for Contemporary Careers

In the constantly evolving career landscape, knowledge about human resource management practices could prove very beneficial for undergraduate college students who want to construct protean careers. With its broad content coverage, the introductory HR course is best suited to teach students about key HR functions and practices instrumental to their career outcomes. The current introductory HR course at the undergraduate level may fall short of this promise as it primarily caters to aspiring HR professionals. We propose to re-imagine the undergraduate introductory HR course from the perspective of students as future employees instead and illustrate the role of HR functions in career progression and how students could use HR knowledge to advance their careers that align with their values. We offer a detailed framework with updated learning goals and sample experiential activities for each major HR topic. We believe that the new approach will make the course more relevant to all students, which could improve learning outcomes and help students construct and manage their protean careers.

Artificial Intelligence Models for Assessing the Evaluation Process of Complex Student Projects

The evaluation of student projects is a difficult task, especially when they involve both a technical and a creative component. We propose an AI-based methodology to help in the evaluation of complex projects in Engineering and Computer Science courses. This methodology is intended to evaluate the assessment process itself allowing to analyze the influence of each variable in the final grade, to discover possible biases, inconsistencies and discrepancies, and to generate appropriate rubrics that help to avoid them. As an example of its application, we consider the evaluation of the projects submitted in an undergraduate introductory course on Computer Science. Using data collected from the evaluation during five academic years, we follow the proposed methodology to create AI models and analyze the main variables which are involved in the assessment of the projects. The proposed methodology can be applied to other courses and degrees, where both technical and creative components are considered to evaluate the projects.

Applying Active Learning in Undergraduate Research Methods

ABSTRACTThis article introduces a bundle of active learning activities for an introductory undergraduate course in research methods. In particular, the activities aim to help students develop core knowledge and skills that provide a foundation for reading and conducting quantitative and qualitative research. Active learning is a pedagogical practice with well-established benefits such as better student attitudes and improved content comprehension and application. I build on this conventional wisdom by applying a student-centred evaluation method, demonstrating that students perceive active learning as an effective complement to traditional lecturing and assignments for learning core methodological topics in political science.

A Syllabi Analysis of CS1 Courses from Brazilian Public Universities

The design and administration of methodological interventions is a possible way to address dropout and failure rates in undergraduate introductory programming courses (CS1). However, to implement such strategies, it is required to identify how CS1 courses are organized and offered to students. In this work, we analyzed 225 syllabi from CS1 courses distributed in 95 Brazilian public universities. We collected these syllabi from Brazilian undergraduate programs with focus on Computer Science aspects. We report context information regarding the most covered topics, most common CS1 course names, when undergraduates take the course, total class hours, and the programming paradigms and languages taught. The results indicate that the Brazilian scenario has its own characteristics that differs from those presented in related work conducted in other countries or world regions. In Brazil, we identified 90% of the analyzed CS1 courses teaches the procedural paradigm, with C as the most common programming language (53% of the total). These results differ from those conducted in other countries where Java and object-oriented are the most common languages and paradigm taught in CS1 courses. We believe that our results can be used to: (1) provide an update to those interested in the Brazilian scenario of CS1 courses; (2) support future interventions in teaching and learning of CS1; and (3) support the Brazilian community in the development of future CS1 syllabi.

Can you see Orion?: knowledge construction and collaborative discourse while problem solving with virtual reality

ABSTRACT Immersive technologies have the potential to play unique roles in the collaborative problem-solving process. To advance research in these contexts, new methods of documenting group collaboration with technology are necessary. The goal of this paper is to develop and utilize a coding scheme that enables investigation of the nature of collaborative interactions within the context of a shared virtual reality (VR) and tablet computer astronomy simulation. This multi-device environment was integrated into the laboratory learning of an undergraduate introductory astronomy course. Two exemplar groups were identified and reviewed for diversity of collaboration and technology interactions. Informed by existing coding practices for collaborative learning, these observations were then used to generate the coding scheme. Coding results reveal that task complexity contributed to an increase in diverse collaboration, and users who switched between technology platforms showed marked differences in their interactions with group members. Moments of discourse when group members were sharing the same simulation view were typically oriented around the acquisition of new knowledge and were often followed by bursts of productive discourse. We discuss the utility of our coding scheme alongside implications of this work via insight into what constitutes understanding in collaborative contexts augmented by immersive and networked technologies.

The next layer: Towards open pedagogy in geospatial education

AbstractOpen‐source software and open data are becoming increasingly popular in the teaching and learning of geographic information science. The cost savings that are derived from using free software over proprietary software are one driving factor, yet the move from “closed” to “open” represents much more than financial austerity—it signifies a broader shift in educational philosophy. This article documents the gradual transition of an introductory undergraduate course in geographic information systems from an entirely closed course to one that has become increasingly open. Having completely adopted the first three layers of open—software, data, and educational resources—the course is now turning toward the next layer: embracing the philosophy of open pedagogy.

Practical Guide to Chemometric Analysis of Optical Spectroscopic Data

The methodology and mathematical treatment of several classic multivariate methods for the analysis of spectroscopic data is demonstrated in a straightforward way that can be used as a basis for teaching an undergraduate introductory course on chemometric analysis. The multivariate techniques of classical least-squares (CLS), principal component regression (PCR), and partial least-squares (PLS), as well as the univariate Beer’s law method have been described and compared, building students’ understanding by starting with the univariate method and progressing step by step into the multivariate methods. Equations for the production of regression vectors from training set spectral data are described and their use demonstrated for the prediction of constituent concentrations on a separate validation set of spectra. Extreme care is taken to ensure consistency in variable formatting of data matrices. This provides a key foundation to understand how spectral data are manipulated using these different mathematical approaches for building quantitative regression models. Each method is applied to a real-world data set, and the results are discussed to show students the types of information that can be gleaned from each method. A training set comprising 20 infrared absorbance spectra containing 3 constituents (benzene, polystyrene, and gasoline) of known composition are used to demonstrate the matrix operations for each regression method. A separate set of 12 real-world napalm samples (containing benzene, polystyrene, and gasoline) are used as a validation set to demonstrate the ability to utilize the regression models on an unknown data set. A toolbox (PNNL Chemometric Toolbox) written in MATLAB language is supplied in the Supporting Information and can be used as a companion for understanding the development and deployment of the chemometric algorithms described in this paper. The data sets of the infrared spectra are also supplied, allowing users to build and inspect the chemometric models on their own. Finally, the Toolbox includes scripts to assist users in loading their own data sets into MATLAB and performing CLS, PCR, and PLS on their data.

Interactions between self‐regulated learning and assessment for learning in an undergraduate introductory computer science course

AbstractMany introductory computer science (CS) courses are intended to address the increased demand for computer literacy and the development of cross‐cutting concepts and practices of computational thinking (CT). Colleges and universities offer introductory CS courses every semester toward this end. The issue is centered on how to support CT learning in a large introductory CS course. To do it, an introductory CS course was designed to enrich CT by embedding short episodes of assessments to facilitate learning (AfL) and to support students’ self‐regulated learning (SRL). This chapter begins by articulating the intricacies of the underlying processes of SRL, principles of AfL, and computational thinking practices in CS. Using the undergraduate introductory CS course referred to above, key practices of SRL and AfL will be illustrated to demonstrate how student learning of CS programming is structured with various online and offline supports. The chapter then concludes by appraising aspects of this CS course with practical suggestions for supporting student SRL and their learning of CS programming.

Meta-Lecture: The educational experience of reversed roles

Abstract According to Bloom’s taxonomy classification create, meant as the production of new and original work, represents the highest and most advanced level of cognitive domain in the learning process. Through creative expression students are encouraged to demonstrate their knowledge by combining elements together and by building something coherent, tangible or conceptual. Meta-Lectureis intended as a non-traditional method to assess mastery of course concepts incorporating short lectures prepared by students, individually, in pair or in a small group, on selected topic, with emphasis on application of course content. This pedagogical approach in teaching is suitable for undergraduate introductory courses as well as for more advanced courses. It represents a student engagement method in both face-to-face and hybrid environment, that aims to improve student commitment and class participation. Through this alternative method, by simulating a professional environment such as public speaking, poster and seminar scientific presentation, students benefit from the experience of reversed role and from instructor’s and audience feedback on the individual evaluation. This report provides introduction to the Meta-Lectureassignment, guidance on the feedback analysis and discussion on the learning process.