Exploring College Students’ Classroom Participation: A Case Study of A Developmental Literacy Classroom

Theriault, Jennifer C.

doi:10.1080/10790195.2019.1638219

Cited by 7 publications

(14 citation statements)

References 32 publications

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“…Students were found to respond to instruction content, to the instructor and to each other. They also made comment on peers in triadic interactions or share personal experience and information in classroom participation (Sedova, 2017 ; Theriault, 2019 ). On the one hand, researchers think that well-designed online activities contribute to enhanced online interaction and students’ participation is closely related to course design and course activities (Chou & He, 2016 ; Tsai et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

“…Both the message quantity and the numbers of regular participants contributed to an active, extensive and persistent online participation over time. Nonetheless, many previous studies showed that very often only a handful of students participated orally while the majority mostly listen passively (Theriault, 2019 ). Besides, about 90% of interactions and participation were made by a small number of students but only around 30% were regular participants.…”

Section: Discussionmentioning

confidence: 99%

“…As to the research methods, Table 1 shows that quantitative, qualitative and mixed research methods are all employed to explore student participation. Depending on different research goals, qualitative methods are utilized to disclose factors impacting student participation or its benefits (Ozkara & Cakir, 2018 ; Sedova, 2017 ; Theriault, 2019 ) while quantitative methods serve to unpack the possible patterns or trends of student participation (Cheng & Lei, 2020 ; Stamm et al, 2017 ) or reveal its relationships with other variables (Crosthwaite et al, 2015 ; Frymier & Houser, 2016 ).…”

Section: Literature Reviewmentioning

confidence: 99%

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Does learning happen? A mixed study of online chat data as an indicator of student participation in an online English course

Qiang

2022

Educ Inf Technol

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Student participation, as a significant indicator of class learning, has been investigated from various perspectives. The present research seeks to explore student participation by drawing on text data from the chat box of an online learning platform. The two main research questions concern the main types of student participation indicated by the online chat data as well as how extensively and frequently students had participated online in class. The written text messages of 84 university students in the chat box were recorded in an online English course for three months in consecutives. The findings revealed that students’ online chat data generally fell into five major types: students’ responses of factual information (62.77%) social interaction (15.74%), phatic communication (9.95%), tech-related messages (7.5%) and class schedule (4.5%). With 89% of participation concerning meaningful interactions and 11% of participation dealing with simple clarification of tech problems and class schedules, the findings suggest a highly active and meaningful online in-class participation. In addition, further descriptive statistics depicted the level of participation in terms of its frequency and breadth. Results showed that the active and meaningful online participation had been persistent over three months with an average of 74.52% regular participating students and average 410 chat messages sent one day. Implications were discussed in relation to the features of student participation.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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Does learning happen? A mixed study of online chat data as an indicator of student participation in an online English course

Qiang

2022

Educ Inf Technol

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“…More specifically, quantity was defined as the number of learning opportunities given to students to take part in all classrooms activities constructively. Dependability relates to having learners who can contribute to different interactions "appropriately, obviously and respectfully" when asked to do so in the classroom, while quality of classroom interaction relates to students who show their cognitive abilities through giving evidence of personal awareness of conceptual and procedural knowledge discussed in the class and this involves some repetition of interactions (Murray & McConachy, 2018;Nura & Zubairu, 2015;Petress, 2006;Rocca, 2010;Theriault, 2019).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

The impact of mathematics learning environment supported by error-analysis activities on classroom interaction

Khasawneh

Al‐Barakat

Almahmoud³

2023

EURASIA J Math Sci Tech Ed

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This study was designed to investigate the effect of mathematics learning environment supported by error-analysis activities on classroom interaction. To achieve this purpose, two classes of seventh grade students (aged 12-13 years) were randomly selected and were assigned into two groups; experimental (number of student=24) and control (number of students=24). The experimental group was exposed to error-analysis activities, whereas the control group studied the same mathematics content without any error-analysis activities. Moreover, two instruments were used to collect the data: an observation checklist including indicators of classroom interaction and a semi-structured interview, after ensuring their validity and reliability.<br /> 14 classes for each group were observed by two observers using an observation checklist. The findings of the study revealed that statistically significant differences were found between the rating means of classroom interaction of the two groups. Moreover, the qualitative analysis of the interviews revealed that the mathematics error-analysis activities contribute to improving the quality of teacher-student, student-student and student-content interaction. They enhance the quality of students’ responses, help students be more engaged in mathematics learning through social interaction and more active in oral communication, improve their classroom predications and discussions and support student-content interaction through sustaining error-analysis to be a learning behavior. Based on these findings, it was recommended that mathematics learning environment supported by error-analysis activities could be adopted as a teaching-learning strategy to improve classroom interaction, which enhances students’ mathematics learning in primary education.

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“…Furthermore, colleges should give students an opportunity for interactions with their instructors and such interactions may be beneficial to working students (Perna, 2010). Theriault, (2019) suggested that colleges should use oral participation as a way to demonstrate interest and keep class active and moving forward particularly when students are not feeling confident in their knowledge or understanding. Brooms ( 2018) Suggests that students should be enhanced with the sense of mattering and belonging on the campus through helping them access sociocultural capital, providing holistic support, and engendering student's persistence.…”

Section: Supporting Employed Studentsmentioning

confidence: 99%

An Assessment of the Employment Among College Students in Tanzania

Ntare¹,

Rujomba²

2021

Bej

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This study empirically assesses employment among college students in Tanzania. It examined the effect of age and gender on student employment, the factors that lead employed people to join undergraduate studies, and identified ways that colleges may use to help employed students to succeed in their studies in Tanzania. Data were collected using questionnaires, interviews and analyzed quantitatively through descriptive analysis and multiple logistic regression. Logistic regression results showed that the employment probability was steadily increasing between ages 18 to 33, but then after it decreases steadily with age at least after age 34, and the male students had an average chance of employment 2.15 times the chance of female students. Descriptive statistics results showed that the factor that leads employed people to join undergraduate studies were: the need for technical skills, knowledge, exposure, job security, social status, job market, job promotion, get new friends, internal motivation, and unemployment. Also, the results showed that the ways to improve education success among employed students were the introduction of evening courses, student interaction with instructors, offering students access to an academic advisor, career counseling, offering weekend courses, increase the students' assessment criteriaâ€™s, involve students in outreach activities, and offering the online courses.

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Exploring College Students’ Classroom Participation: A Case Study of A Developmental Literacy Classroom

Cited by 7 publications

References 32 publications

Does learning happen? A mixed study of online chat data as an indicator of student participation in an online English course

Does learning happen? A mixed study of online chat data as an indicator of student participation in an online English course

The impact of mathematics learning environment supported by error-analysis activities on classroom interaction

An Assessment of the Employment Among College Students in Tanzania

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