Large or Small Classes?

This paper explores the case study experience in large and small undergraduate classes, with a view to identifying and comparing the challenges which exist in each setting. Using open-ended student surveys and lecturer reflections, the study compares how students in large and small classes, drawn from similar backgrounds, experienced two case events. Contrary to expectations, positive responses were reported in the large class setting as well as in the small class setting. However, managerial factors dominated in the large classes, reducing opportunities for engagement. Different class dynamics were also observed in each setting. Significant differences in expectations were identified between students in large and small class settings regarding participation and interaction. Raising the expectations of students in large classes emerged as a challenge to educators.

“That’s it for today”: Academic lecture closings and the impact of class size

Compelling evidence indicates that “active learning” (learning by doing) is an effective pedagogy regardless of discipline or class size, and can be particularly effective with diverse students. This study investigated active learning practices in 64 classes at the University of Hawai‘i at Mānoa, a US university with a highly diverse student body, using a “Passivity Indicator” (PI: ratio of class time spent in passive activities to total class time). For all classes, the mean PI was 43%. Statistical analysis reveals no significant differences in the PI of classes taught in STEM vs. non-STEM disciplines, or between upper vs. lower division courses. However, the PI in larger classes was found to be significantly greater than in small classes (64% vs. 39%, respectively; p=0.02). Moreover, classroom activities aligned with an active learning standard in Language and Literacy Development (e.g., students answering questions) occurred twice as often in small (24%) vs. large classes (12%, with p=0.02). Altogether, these findings indicate an opportunity for more active learning in large classes. We present a range of research-based pedagogical strategies that can be readily implemented in large classrooms, and encourage instructors to use their implementation as research opportunities to gather data on student success.

College and university students' verbal participation in larger classes (60 students or more) seems to be less than in smaller classes (Karp and Yoels 1976, p. 197; McKeachie 1986, p. 183). This impression fits with common sense and with the additional finding that large class size is an important reason why students choose not to participate (Karp and Yoels 1976, p. 200). Little research has been conducted on this matter, but there seem to be at least two reasons why students in large classes participate less: lack of sufficient incentives for students and the instructor's lack of ability to keep accurate track of participation. Increasing class size gradually raises anxiety about speaking before a larger audience, regardless of knowledge about the subject. Also some students are afraid to err and to seem unintelligent. Others may be afraid to seem too smart and to appear to be a nerd or a brain. If a sufficient incentive can be found, it may overcome this anxiety, even in large classes. As for the instructor, he or she may be able to keep track of participation by students in smaller classes where all members are known fairly soon by name, but in larger classes such knowledge of names tends to be slower in coming and to be spotty at best (especially in very large classes, 200 or more). Thus the accurate tracking of participation is difficult. Experts argue that students learn better when their learning is active and involves talking and interacting (Goldsmid and Wilson 1980, p. 293) and when they have more opportunities for feedback (McKeachie 1986, p. 27). Some of these experts suggest ways to obtain more participation in large classes. McKeachie (1986, p. 189) recommends the use of buzz groups (small-group discussion), problems posting (writing problems on the blackboard), and role playing. I have been using a technique that I have not seen mentioned in the literature and that I would like to share. Students make brief notes of their class participation each class day, turn them in at the end of class, and receive class participation credit for each acceptable item up to three per session. This is an incentive system that encourages more participation. The approach is significant in dealing effectively, simply, and efficiently with a widespread problem: poor participation by students in classes of 60 or more. This technique encourages better students to exert more effort in class participation than they would otherwise, drawing on their desire to earn a good grade. The methodology of this paper is simple observation, primarily qualitative but occasionally quantitative. I felt the need for a technique of encouraging and keeping track of participation in classes of 70-odd students. I have experimented with this technique for several years and have compared classes in the same course and of the same size with and without the technique to judge its impact.

Due to increasing student enrollments and limited resources, small classes are evermore being replaced with large lectures. It is therefore essential to quality educational programs to address the challenges of student learning and engagement in large classes. This paper explains connections between basic learning research and practical strategies for engaging students in large engineering classrooms. First, we ground proposed instructional strategies with theory and empirical evidence on such key matters as how students represent ideas in memory, how these representations are elaborated and perfected over time, and how stored information can be retrieved for use. This helps us to understand how students learn to monitor and control their own learning and how large class environments can be approached as sites for significant learning. We discuss how electronic student response devices (clickers) have been useful for generating in-class interaction and active learning in large classes for individual and team activities. How to administer beneficial team-based projects for large classes is also presented, including: real-world problems that require teams to investigate and understand contemporary issues such as sustainability, working with industry, and third- world countries. Finally, personal style and characteristics of faculty who are successful with large classes is discussed.

On the basis of the blended learning mode, a comparative analysis of the formative assessment, summative assessment and degree of course objectives achievement of curriculum evaluation in the large-class and small-class teaching process of college physics in local universities is carried out. Furthermore, it demonstrates that small-class teaching is easier to achieve the transformation of the “student-centred” teaching mode, the effective achievement of the teaching goals of knowledge inquiry and ability building in college physics, and the diversification of teaching evaluation methods. The experiments show that the percentage of students in the small classes (31%) within the 90 to 100 points range is much higher than that in the large classes (18%) in terms of formative assessments. Meanwhile, the proportion of over passing grades (>60) in small classes is 19% higher than in large classes on summative assessments. Finally, the overall achievement degree in small-class teaching has a 5% higher achievement than in large-class teaching.

Large classes are a reality and an ongoing issue in higher education in most countries. Theoretically, a large class is any class where teachers face challenges in teaching, assessing students’ performance and managing the class due to the number of students. The paper will focus on assessment in large classes, looking at some familiar methods, as well as researching the possibilities of innovative technologies as useful assessment tools, self-evaluation using new technologies, and collaborative learning. The selection of the right methods for assessment is essential for meeting students’ needs without compromising the very integrity of the entire process; hence, a questionnaire will be utilized to investigate the opinions of teachers and students on their assessment process. The results will offer some new assessment possibilities that may compensate for the lack of adequate student-teacher contact and interaction usually present in small classes, but not always in large classes.

The Effect of EFL Large Classes on Yarmouk University Students' Achievement

Seston in the impounded North Anna River (NAR) was analyzed and compared to that in the free-flowing South Anna River (SAR) in Virginia, U.S.A. A wet filtration technique was used to separate seston into five size classes. The overall quantity of organic seston was much lower in the NAR than in the SAR. The seston in the NAR was composed of more living organisms, in particular zooplankters in the medium large (234–864 µm) and small (105–234 µm) size classes and diatoms and other algae in the fine (43–105 µm) and very fine (25–43 µm) size classes. The percentage of zooplankton declined sharply before reaching the downstream study site (32 km). The seston in the NAR tended to consist of slightly larger particles, but 80–85% of the seston in both rivers was in the ultrafine (0.45–25 µm) size class, which was almost entirely composed of detritus. One indication of seston food quality, the organic/inorganic ratio, was considerably higher for the medium large and small size classes in the NAR immediately below the dam and for the fine and very fine size classes farther downstream. Another indication of food quality, the usable caloric content, showed that the seston in the NAR contained considerably less total assimilable energy as far as 32 km downstream from the dam, but that the medium large and small size classes were rich in assimilable energy immediately below the dam because of zooplankton released from the reservoir. Thus, the overall quantity and quality of seston was lower in the NAR, but the quality of the seston, for at least a short distance below the dam, was higher in a well-defined size range that can be effectively utilized by certain filter feeders.

A previous study by Bieman et al., investigated whether large, object-oriented classes were more susceptible to change than smaller classes. The measure of change used in the study was the frequency with which the features of a class had been changed over a specific period of time. From a refactoring perspective, the frequency of class change is of value But even for a relatively simple refactoring such as 'rename method', multiple classes may undergo minor modification without any net increase in class (and system) size. In this paper, we suggest that the combination of 'versions of a class and number of added lines of code ' in the bad code 'smell' detection process may give a better impression of which classes are most suitable candidates for refactoring; as such, effort in detecting bad code smells should apply to classes with a high growth rate as well as a high change frequency. To support our investigation, data relating to changes from 161 Java classes was collected. Results concluded that it is not necessarily the case that large classes are more change-prone than relatively smaller classes. Moreover, the bad code smell detection process is informed by using the combination of change frequency and class size as a heuristic.

This study used Q‐methodology to solicit students’ descriptions of specific teachers they perceived as effective and ineffective in small and large classes. Results revealed (a) that students perceived different types of effective and ineffective teachers rather than one type and (b) that there were few differences between teachers of small and large classes. Overall, the findings suggest that the combination of behaviors, including the presence of various positive behaviors and the absence of other negative behaviors, appears more important in determining teacher effectiveness than any individual behaviors.

Total Volatile Base Nitrogen (TVB-N) and Trimethylamine Nitrogen (TMA-N) contents of Vetki (Lates calcarifer) were investigated following Conway’s Microdiffusion technique at 4 hour interval in Fish Quality Control Laboratory, Fisheries and Marine Resource Technology Discipline, Khulna University. Observed TVB-N and TMA-N value did not vary significantly among different size classes. At fresh condition, TVB-N content was observed as 11.106±0.8 mg, 11.162±0.8 mg, and 11.162±0.8 mg in small, medium and large size classes of fish respectively and it increased to 59.087±0.8 mg, 68.417±1.5 mg and 75.967±2.7 mg for 100 g-1 respectively at complete spoilage stage (after 28 hrs). At fresh condition, TMA–N content was 6.7±0.016 mg, 11.069±1.79 mg and 11.172±1.01 mg for 100 g-1 in small, medium and large size classes of fish respectively and it increased to 48.893±3.01 mg, 52.492±.089 mg and 57.717±1.95 mg for 100 g-1 respectively at complete spoilage stage. TVB-N and TMA-N values started to increase gradually in all size groups with the passage of time but the rate of increase became faster after 20th hour and continued till the final stage was reached.

Large and mixed‐ability classes have always been an issue for English language teachers. Although small classes are desirable and provide ample opportunities for students to interact, teaching a large class of students is inevitable in many countries around the world. Even large classes can be taught effectively. Teachers only need to make maximum use of the rich resources that a large mixed‐ability class contains.

Asynchronous online discussion is a learning activity commonly used in online teaching. The way instructors participate in asynchronous online discussions significantly impacts students' learning outcomes. This systematic review aims to determine the effects of instructor participation in asynchronous online discussions on student performance by analysing 25 relevant studies in the past twelve years (2011–22). The findings show that the research was focused on the presence, frequency and type of instructor participation. The effects of instructor participation on student performance were mixed and concentrated in five main aspects: the quantity of student participation, the quality of student participation, student achievements, student emotions and student learning time. Not only the teaching experience of instructors but also course content, learning objectives, class sizes and learner characteristics influenced the effects. Based on the findings, several recommendations were made to help instructors effectively participate in asynchronous online discussions, thereby contributing to improving the quality of online education. Practitioner notes What is already known about this topic Asynchronous online discussion is a learning activity commonly used in online teaching. The way instructors participate in asynchronous online discussions significantly impacts students' learning outcomes. What this paper adds Previous research on instructor participation in asynchronous online discussions and student performance primarily focuses on the presence, frequency and type of instructor participation. The impact of instructor participation on student performance is mixed and concentrated in the following main areas: Quantity of student participation Quality of student participation Student achievements Student emotions Student learning time The effects of instructor participation are influenced not only by the teaching experience of instructors but also by: Course content Learning objectives Class sizes Learner characteristics Implications for practice and/or policy Instructors should participate in asynchronous online discussions based on the class sizes, more in small classes (within 15 students) and less in large classes (more than 30 students). If it is possible, divide the large classes into small discussion groups. Instructors should initiate discussions with heuristic and interesting open‐ended questions, gradually release control and give the central position to students and intervene only when necessary (eg, keep discussions on track, provide correct information, extend discussions, mediate conflicts, etc). Instructors should apply appropriate facilitation strategies (eg, establish detailed discussion rubrics, grade student posts and provide regular individual feedback). Instructors should use more instructional comments and supplement them with sincere rather than perfunctory social comments.

<p dir="ltr">Generative AI is gradually becoming ubiquitous in our lives as it is integrated into word processing and office tools with multimodal capabilities. Concerns regarding the lack of human accountability, equity and ownership regarding the use of genAI tools in students’ work have been raised. This opinion piece argues that educators should aim to use the genAI tools to challenge students to think critically and connectedly, and to consider the implications of their decisions to their organizations and society. Two use cases, one representing soft skills taught in small classes and the other on hard skills taught in large classes, are shared. These cases reflect how students are taught to think critically using the Paul-Elder framework and systems thinking habits so that they do not think in silos. Via discussions and questioning activities in class, students learn to be strategic and critical when using genAI and to consciously consider the impact of their work on others.</p>