Introductory Course Research Articles

Comparative Analysis of the Effectiveness of Informatics Course Learning Utilizing Chatgpt

This study examined the effectiveness of conventional teaching methods and ChatGPT in an introductory Algorithms and Programming course at the university level. ChatGPT, an AI-based NLP technology, assisted students in understanding course material through automated responses. However, its effectiveness relative to conventional methods required further evaluation, particularly concerning motivation, interaction, self-regulation, instructional structure, and the instructor's role. Using a sample of 10 students for pretest-posttest analysis, 38 respondents for the User Experience Questionnaire (UEQ), and accuracy analysis via prompt engineering, the results revealed that conventional methods better enhanced motivation and interaction. ChatGPT demonstrated strengths in attractiveness (1.982) and efficiency (2.053) but scored lower in accuracy (1.395) and novelty (1.053). Prompt engineering significantly improved response accuracy when tailored to learning modules, highlighting the importance of precise inputs. The findings suggested that while ChatGPT excelled as a supplementary tool, it was less effective as a standalone teaching method. This study contributed to the growing field of educational technology by providing insights into the integration of AI tools in learning environments.

Exploring how course social and cultural environmental features influence student engagement in STEM active learning courses: a control–value theory approach

BackgroundActive learning, on average, increases student performance in STEM courses. Yet, there is also large variation in the effectiveness of these implementations. A consistent goal of active learning is moving students towards becoming active constructors of their knowledge. This emphasis means student engagement is of central importance. Thus, variation in student engagement could help explain variation in outcomes from active learning. In this study, we employ Pekrun’s Control–Value Theory to examine the impact of four aspects of course social and cultural environments on student engagement. This theory posits that social and cultural features of the course environment influence students’ appraisals of their ability to control their academic outcomes from the course and the value they see in those outcomes. Control and value in turn influence the emotions students experience in the course and their behaviors. We selected four features of the course environment suggested in the literature to be important in active learning courses: course goal structure, relevance of course content, students’ trust in their instructor, and perceived course competition.ResultsWe surveyed students in 13 introductory STEM courses. We used structural equation modeling to map how features of the course environment related to control, value, and academic emotions, as well as how control, value, and academic emotions influenced engagement. We found engagement was positively related to control and value as well as the emotion of curiosity. Engagement was negatively related to the emotion of boredom. Importantly, features of the course environment influenced these four variables. All features influenced control: goal structure, relevance, and instructor trust increased it, while competition decreased it. All features except competition were related positively to value. Relevance and instructor trust increased curiosity. Goal structure, relevance, and instructor trust all reduced boredom, while competition increased it.ConclusionOverall, our study suggests that the way instructors structure the social and cultural environment in active learning courses can impact engagement. Building positive instructor–student relationships, reducing course competition, emphasizing mastery and the relevance of the course to students can all increase engagement in course activities.

Investigating the Effects of Cognitive Style on the Motivation of Students Enrolled in a Team-Based Learning Formatted Agricultural Mechanics Course at Louisiana State University

Educators have a plethora of teaching methods that allow them to tailor the learning environment to meet students’ needs. One novel instructional approach that has grown in popularity in U.S. higher education has been the flipped classroom approach, which has become a popular way to embrace a student-centered learning environment. Of the various types of flipped classrooms, team-based learning allows students to learn content outside of classroom time and spend more time doing hands-on activities as a team in a laboratory environment. This study aimed to describe the effect of cognitive style on the motivation of undergraduate students enrolled in an introductory agricultural mechanics course at Louisiana State University. Descriptive statistics, including means, frequencies, and standard deviations, were utilized to test the hypothesis and gain a holistic understanding of the data. We also conducted a Mann-Whitney U test to determine if a statistically significant difference existed between motivation and cognitive style. No statistically significant differences were found between cognitive style and motivation. However, the more innovative students in this investigation had higher motivation scores than those identified as more adaptive.

Content knowledge attainment in English medium instruction: Does academic English literacy matter?

This study investigates the relationship between students’ English language proficiency, their reported levels of academic English literacy, prior content knowledge and their attainment of content knowledge in English medium instruction (EMI). The study also examines students’ perceptions of difficulties with academic English literacy at different levels of English language proficiency. Pre-course and post-course content tests were administered to 27 EMI students in an introductory Chemistry course at a university in Tokyo, Japan. The test results were triangulated with data from a quantitative measure of reported academic literacy and follow-up interviews to explore perceptions of ease and difficulties for academic language skills (i.e. reading, listening, speaking and writing). The quantitative findings indicated that students’ proficiency statistically significantly predicted post-test scores. Interviews with students corroborated this finding, illustrating the specific difficulties in academic language literacy faced by students with lower proficiency. However, proficiency alone did not determine success as other factors, such as previous exposure to EMI and prior content knowledge, played significant roles. The study found a non-linear relationship between reported difficulties with academic English literacy and test outcomes, indicating that students who reported fewer academic difficulties were not necessarily more successful in gaining content knowledge than those facing significant challenges in academic language tasks. The findings emphasise that academic support in EMI programs should not solely focus on test outcomes but also address the broader challenges students face with academic English literacy. Implications are discussed regarding language support, EMI curriculum planning and future research directions.

Generative AI for Data Science 101: Coding Without Learning to Code

Should one teach coding in a required introductory statistics and data science class for non-major students? Many professors advise against it, considering it a distraction from the important and challenging statistical topics that need to be covered. By contrast, other professors argue that the ability to interact flexibly with data will inspire students with a lasting love of the subject and a continued commitment to the material beyond the introductory course. With the release of large language models that write code, we saw an opportunity for a middle ground, which we tried in Fall 2023 in a required introductory data science course in our school’s full-time MBA program. We taught students how to write English prompts to the artificial intelligence tool GitHub Copilot that could be turned into R code and executed. In this short article, we report on our experience using this new approach.

Examining Initial Expectations, Preferences, and Concerns of Diverse Students in an Introductory Statistics Course to Inform Course Improvements

A survey conducted at Cornell University explored the expectations, preferences, and concerns of students entering a large introductory statistics course. They were asked the first week of the term what they anticipated being similar or different from their high school statistics (or comparable math) class. Most expected the college class would be more difficult and they would have to do more independent learning. They expressed a preference to spend 66% of class time in a lecture and 34% in active learning. Students were overall very concerned about the course being too fast paced and too difficult and that they would receive too few in-depth explanations. Presentiments were also compared within demographic subgroups. Female students consistently showed higher rates of concern than male students. Asian students were most concerned about knowing what to study, while underrepresented students were primarily concerned about the difficulty of the subject. International students worried most about receiving too few in-depth explanations, while first-generation students were apprehensive about being expected to do too much independent learning. Resources to address specific delineated issues are included.

An Investigation Designed to Teach Statistical Thinking in the Midst of the COVID-19 Pandemic: Are Teens Living Like Vampires?

Students can learn to think statistically by being actively engaged in investigations that use real data to answer a question. Projects that explore familiar questions that students intuitively understand can spark their interest and are ideal vehicles to teach data literacy. This article shares a project that was used in an introductory statistics course to investigate if young people were sleep-deprived or had altered their sleep schedules during the COVID-19 pandemic. Students’ interest was piqued and they were highly motivated to learn how the pandemic had impacted their peers. Working with an authentic, relatable context, helped students make conjectures. I describe how students used descriptive and inferential statistics to understand whether their peers’ sleep schedules had changed during the pandemic. Pedagogical practices that are shared helped build students’ confidence and decrease the sense of overwhelm that can accompany comprehensive investigative projects. In addition to the significant gains students made, modeling how statistics research is done outside the classroom, investigative projects such as this can provide teachers with valuable insights and an alternative way to assess students’ ability to think like empirical researchers.

Qualitative analysis of peer reviews of a large introductory programming course

ABSTRACT Background and Context Getting timely feedback is important for learning. However, providing individual feedback is a problem in large courses. Peer code review can address this issue and has shown to offer various advantages such as enhanced collaboration among students, improved coding skills, and seeing and criticizing different solution strategies. Objectives The goal is to gain a comprehensive understanding of the contents of voluntary peer reviews and students’ review skills in a first-semester university-based introductory programming course with about 900 enrolled students and no special support or training for conducting reviews. Method A qualitative analysis was conducted on 215 randomly sampled peer reviews as well as the associated code submissions. Qualitative factors such as frequencies of corrections, coding tips, questions, “empty” submissions/feedback, and the sentiment are analyzed. Furthermore, errors in the submissions and mentioned errors in the reviews are investigated exploratively. Findings The analysis results indicate that, in general, students are better in detecting incorrect solutions as incorrect than correct submissions as correct. The feedback is neutral to positive contains a lot of praise, but is rather short and uncertainty is expressed quite often. Students seem to be very nice to each other. Submissions without intensive solution attempts and “empty” reviews are quite rare. Students can correct errors and provide coding tips, however, often do not see subtle errors such as partly incorrect algorithms, typos in method names, or output formatting errors. Implications The results help to train students to write better reviews and to inform educators on how to provide better instruction or support for peer review.

Experiential Learning about Database Design in the MLIS Curriculum: Software and Instructional Design for Threshold Knowledge

With almost all MLIS and similar degree programs having a required course covering database design, it is critical to develop curriculum that engages students in learning essential concepts and how to implement designs. We report on a project that explored how essential knowledge about database design can be taught effectively through experiential learning activities involving collaborative groupwork and using database software to build small databases and search forms. The focus is an existing required introductory course on information retrieval system design, in which students learn about database design concepts and implement their designs in browser-based software, building the database structure, content, and search forms. They learn about critical concepts in database design, including eliciting user needs and requirements, prototyping, teamwork, and iterative testing and evaluation. The project had two aims: to select new database software to use as a learning tool in the course and to redesign course assignments so that learning experiences would be enhanced. The project led to important findings about the student learning experiences, to improvements in the curriculum, and to recommendations for educators involved in similar courses.

Promotion of Student Success and Positive Chemistry Course Perception through Frequent Metacognitive Reporting.

Explicit metacognitive interventions in undergraduate chemistry courses have been shown to improve student outcomes. Less studied have been the outcomes of students who implicitly and frequently practice metacognition and the resultant effects on the student-instructor relationship. In this project set within a large enrollment introductory chemistry course, we elevated student voice and enhanced student-instructor communication through weekly metacognitive reporting to study the characteristics of reporting students and their perceptions of the effects of metacognitive reporting. Data on course success and gender of reporting relative to non-reporting students were quantitatively analyzed using standard statistical techniques. Inductive thematic coding was used to qualitatively assess student responses to open-ended post-survey questions on perceived value of metacognitive reporting. Reporting students finished the semester with a final course grade point average 0.64 points higher than non-reporting students. In addition, reporting students were more successful (more ABC grades) than non-reporting students though small effect sizes and lack of directional causality limit data interpretation. However, female students tended to engage in reporting at a higher rate than did male students. Metacognitive reporting helped to establish a more positive and productive student-instructor relationship via enhanced student communication (i.e., student voice) that informed just-in-time teaching modifications. Students indicated that the metacognitive reporting assisted them in focusing their studies on more challenging topics and in modifying their study habits. In addition, students recognized that their instructors were reading and responding to the reports, which improved overall student-instructor interactions and their view of the instructor as beneficent. Based on these findings, it is recommended that instructors create frequent, low-stakes assignments built into the course structure to support their students' implicit use of metacognition with the broad goal of growing metacognitive strategies over time.

Effects of nursing interventions applied at night on sleep quality and sleep effort of patients in the intensive care unit

ABSTRACT This study aimed to evaluate the effect of nursing care interventions applied at night on the sleep quality and sleep effort of intensive care patients. This study is descriptive and cross-sectional in nature. The sample size consists of 82 intensive care patients. Personal information form, Glasgow Coma Scale, Richard-Campbell Sleep Scale, Glasgow Sleep Effort Scale were applied to the patients. In the analysis of the data, Independent Samples t test, One-Way Analysis of Variance (ANOVA), Pearson Correlation test, and multilinear regression analysis were used. Based on the findings of the examined patients, it was concluded that care interventions may disrupt the sleep of intensive care patients. It is thought that determining the care interventions that disrupt the sleep of intensive care patients may contribute to better planning of care and preserving the sleep patterns of the patients. Basd on our results, nursing education programs and intensive care unit introductory courses should be reviewed to understand the importance of sleep. In this context, reducing unnecessary interventions and diagnostic procedures at night, evaluating and managing pain, using questionnaires for daily bedside evaluation of sleep quality, and implementing interventions that support sleep quality and sleep should be an integral part of nursing care. Insomnia is a significant stressor in the intensive care unit. Therefore, it is important for nurses, who are primarily responsible for care, to determine the sleep quality of patients, evaluate the factors that reduce sleep quality, and implement preventive interventions to ensure patient comfort. It is expected that this study will lead to plans for grouping nursing care interventions in a way that will not affect sleep.

Evaluating student understanding of core pharmacokinetic concepts.

Both educators and graduates have expressed concern about a perceived pharmacology knowledge gap that includes difficulty applying fundamental principles to clinical and research problems. Consequently, we sought to determine the extent to which current students can explain the meaning of, and appropriately apply, a subset of core concepts, and to identify any misconceptions arising from the responses. Of the twenty-four pharmacology core concepts arising from the recent international collaboration, four pharmacokinetic concepts were chosen, namely drug bioavailability, drug clearance, volume of distribution, and steady-state concentration. A total of 318 students from 11 universities across seven countries chose to participate in this study. Expert analysts identified the essential elements for each concept, then independently assessed each student's response. Teams of two experts compared their evaluations to reach a consensus and grouped misconceptions thematically. For each core concept, less than 30% of students provided responses that encompassed all essential elements. Participants found drug clearance most challenging, generally conflating it with the rate of elimination, whereas they demonstrated a better understanding of drug bioavailability. There were 34 misconception themes coded in a total of 813 statements, with volume of distribution and drug clearance producing the highest numbers (13 and 12, respectively). Overall, results suggest that students found it easier to apply the concept than to explain its meaning, which might reflect the shift from didactic to active learning approaches. These findings may be useful for educators who are developing introductory pharmacokinetic courses by providing conceptual focus and revealing common misconceptions to explicitly address.

Innovative assessment based on multimedia proofs and social network sharing for introductory engineering courses

Innovative assessment based on multimedia proofs and social network sharing for introductory engineering courses

Effective instructor feedback does not always promote better public speaking outcomes: the importance of self-efficacy and feedback orientation(s) in the introductory course

ABSTRACT Research has yet to fully explain the processes through which feedback affects student outcomes. The majority of research has also focused on feedback from an instructor's perspective. Guided by feedback intervention theory (FIT; Kluger, A. N., & DeNisi, A. [1996]. The effect of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory. Psychological Bulletin, 119[2], 254–284. https://doi.org/10.1037/0033-2909.119.2.254), and using longitudinal online survey data from students in an undergraduate introductory communication course at a 4-year university (N = 2,523), we found that self-efficacy mediated the relationship between perceived feedback effectiveness and both PSA and CC, playing a positive role in increasing students’ CC and decreasing their PSA. Various feedback orientations, especially feedback sensitivity and confidentiality, exerted moderating and/or conditional indirect effects on our proposed feedback cycle. These findings advance scholarly knowledge of the feedback cycle according to FIT, repositioning self-efficacy as a critical mediator. They also speak to the importance of understanding how students’ feedback orientations can dampen or strengthen the positive impact of effective feedback on public speaking outcomes. Additional theoretical implications and pedagogical recommendations are discussed.

The relationship between chemistry achievement emotions and chemistry achievement: a moderated mediation model

Chemistry, an introductory course of STEM courses and a critical subject in China's curriculum standards, plays a pivotal role in students' lifelong learning and development. This study explored the relationship...

Equipping college students with statistical literacy under the massification of higher education

Big data analysis has become an essential decision-making tool across various sectors, with statistics serving as the critical knowledge base. However, many college students, especially those with weaker mathematical skills, experience anxiety about statistics. This study explores strategies to improve statistical literacy among such students. Using a questionnaire survey, it focuses on an introductory statistics course at a university in Taiwan, applying the Partial Least Squares method to test the structural equation model. The findings suggest that integrating statistical software into instruction, conducting frequent formative assessments, and designing test content conducive to learning can enhance students' perceived learning outcomes and self-efficacy. Despite limitations like small sample size and representativeness, the study highlights that statistical software not only aids learning but also develops practical skills for real-world application. Open-book exams are recommended, but multiple assessment methods should be used to ensure fairness. The study concludes that while statistics anxiety is difficult to alleviate, enhancing self-efficacy can improve students' attitudes toward statistics. It proposes scaffolding strategies to support students with low mathematical skills, ultimately improving their statistical literacy and confidence.

Engineering education: Nurturing a holistic skill set for future success through an introductory course

The choice of post-secondary courses is heavily influenced by individuals' perceptions of their chosen discipline. Freshmen often bring preconceived notions about engineering, impacting their course preferences. Students excelling in Physics and Mathematics typically gravitate towards engineering, believing it provides a competitive advantage. However, beyond technical skills, engineering demands proficiency in soft skills like problem-solving, teamwork, and creativity. This article, authored by teaching assistants of an introductory engineering design and communication course, delves into the holistic aspects of engineering. The course aims to provide a comprehensive understanding of engineering by emphasizing critical skills such as project management, communication, teamwork, adaptability, safety, and ethics. Despite the belief that a strong background in physics and mathematics suffices for engineering success, this course stresses the importance of a well-rounded skill set. The authors emphasize the necessity of developing non-technical skills for a successful engineering career, challenging the conventional narrative, and advocating for a more comprehensive approach to engineering education. The authors underscore the importance of students' perspectives on these concepts and provide their recommendations and a call to action to improve the student perception of such courses.

Incorporating Sustainability Principles into the First-Year Engineering Design Curriculum for International Students

Courses focusing on engineering design present an excellent opportunity for the introduction of the concepts of sustainability. The purpose of the proposed work is to enhance students’ understanding of sustainability through a project-based approach. For that purpose we developed a new exploratory project consisting of 3 possible real-world inspired case studies and implemented them in the introductory engineering design course. Results show that nearly all of the participating students generally consider sustainability a key aspect of their education; however, the particularities of student opinions with respect to sustainability outcomes in designs largely vary and seem to depend on the goals and design focus of each program. Our analyses show that the project-based learning course had a moderate to large impact on student competencies including systems thinking, environmental literacy, responsible business and economy, social responsibility, environmental impact measurement, materials choice, design, critical thinking, and communication and teamwork. The particular design project implemented here is an excellent learning tool for first-year engineering students, directing them to include sustainability considerations in their products and systems design. It also creates a space for open discussions about global considerations related to sustainability, together with an opportunity for international students to share their personal experience and previous exposure to sustainability issues.

Hands-on training about data clustering with orange data mining toolbox.

Data clustering is a core data science approach widely used and referenced in the scientific literature. Its algorithms are often intuitive and can lead to exciting, insightful results that are easy to interpret. For these reasons, data clustering techniques could be the first method encountered in data science training. This paper proposes a hands-on approach to data clustering training suitable for introductory courses. The education approach features problem-based training that starts with the data and gradually introduces various data processing and analysis methods, illustrating them through visual representations of data and models. The proposed training is suitable for a general audience, does not require a background in statistics, mathematics, or computer science, and aims to engage the audience through practical examples, an exploratory approach to data analysis with visual analysis, experimentation, and a gentle learning curve. The manuscript details the pedagogical units of the training, motivates them through the sequence of methods introduced, and proposes data sets and data analysis workflows to be explored in the class.

A structured approach to developing an introductory statistics course for graduate students: Using data to teach about data

A structured approach to developing an introductory statistics course for graduate students: Using data to teach about data