Research Article
Sumie Tsz Sum Chan, Noble Po Kan Lo, Alan Man Him Wong
CONT ED TECHNOLOGY, Volume 16, Issue 4, Article No: ep541
ABSTRACT
This paper investigates the effects of large language model (LLM) based feedback on the essay writing proficiency of university students in Hong Kong. It focuses on exploring the potential improvements that generative artificial intelligence (AI) can bring to student essay revisions, its effect on student engagement with writing tasks, and the emotions students experience while undergoing the process of revising written work. Utilizing a randomized controlled trial, it draws comparisons between the experiences and performance of 918 language students at a Hong Kong university, some of whom received generated feedback (GPT-3.5-turbo LLM) and some of whom did not. The impact of AI-generated feedback is assessed not only through quantifiable metrics, entailing statistical analysis of the impact of AI feedback on essay grading, but also through subjective indices, student surveys that captured motivational levels and emotional states, as well as thematic analysis of interviews with participating students. The incorporation of AI-generated feedback into the revision process demonstrated significant improvements in the caliber of students’ essays. The quantitative data suggests notable effect sizes of statistical significance, while qualitative feedback from students highlights increases in engagement and motivation as well as a mixed emotional experience during revision among those who received AI feedback.
Keywords: LLMs, feedback, student engagement, student motivation, generative AI
Review Article
Sergei P. Zhdanov, Kseniia M. Baranova, Natalia Udina, Artem E. Terpugov, Elena V. Lobanova, Oksana V. Zakharova
CONT ED TECHNOLOGY, Volume 14, Issue 3, Article No: ep369
ABSTRACT
The COVID-19 outbreak has wreaked havoc on educational systems on a scale never seen before in history. The closure of schools and other institutions of learning has impacted 94% of the world’s student population. Even school closures, such as those that occur during the summer, have a significant effect on children’s academic ability. The word “learning loss” refers to any loss of information and abilities, whether specific or generic. By Fall 2020, extended absences from school will have a detrimental effect on student achievement. Learning loss is commonly addressed when schools close for extended periods of time during the summer, natural catastrophes, or epidemics. Even brief school closures might result in significant loss of learning. Due to the global nature of the COVID-19 epidemic, special attention was devoted to learning losses.
During the pandemic, learning loss occurs as a result of kids studying at home due to school closures. School closures do not have to result in an equal loss of learning for all students. The variables that contribute to learning loss include “change in teaching methods”, “opportunities to reach education”, “less time for learning”, and “emotional factors”. Reduced instructional time–provided by teachers in accordance with the national curriculum–is likely to result in loss of learning. Due to the disparate scales used in the studies, it is hard to compare the magnitudes of learning losses. However, based on the data from the studies, it is reasonable to assume that these nations are investigating learning losses and that they exist. As a result, there is convincing evidence that students lose more information during lockdown than they do over the course of a normal school year. The elements causing learning losses differ according to context. With the reopening of schools, it is important to establish the actual magnitude of learning losses and to implement remedial measures in order to avoid the emergence of medium- and long-term educational difficulties.
Keywords: learning losses, change in teaching methods, opportunities to reach education, less time for learning, less control/feedback, emotional factors
Research Article
Ozlem Baydas Onlu, Mustafa Serkan Abdusselam, Rabia Meryem Yilmaz
CONT ED TECHNOLOGY, Volume 14, Issue 3, Article No: ep368
ABSTRACT
This study aimed to develop the “Students’ Perception of Instructional Feedback Scale” (SPIFS) determining a framework related to the perception of instructional feedback by students. The sequential exploratory mixed method was used in the study. The study was conducted during the instructional design course offered to sophomores in the Department of Computer Education and Instructional Technology at two different universities. Accordingly, firstly a scale consisting of 31 items with Likert-type responses was prepared based on the literature review. Validity and reliability analyses of the scale were completed with a total of 231 participants. After necessary steps were applied in exploratory factor analysis (EFA, n=100), a structure with three factors and 19 items was established. The internal consistency analysis (Cronbach’s alpha), which was applied to the factors obtained and the whole scale, showed the scale to be reliable (whole scale α=.85, 1st factor (mastery, 8 items) α=.92, 2nd factor (positive affect, 6 items) α=.90, and 3rd factor (negative affect, 5 items) α=.96). Confirmatory factor analysis (CFA) was performed (n=131). The structure established through EFA was tested via CFA. The results indicated that the developed structure had acceptable fit (RMSEA=.08, CFI=.91, and RMR=.03).
Keywords: instructional feedback scale, students’ perception, exploratory factor analysis, confirmatory factor analysis
Research Article
Sanna Elina Oinas, Helena Thuneberg, Mari-Pauliina Vainikainen, Risto Hotulainen
CONT ED TECHNOLOGY, Volume 12, Issue 2, Article No: ep271
ABSTRACT
As a variety of commercial educational applications are currently being taken into daily use to provide technology-enhanced feedback, research is needed to observe whether pedagogical evidence of the impact of feedback on learning and well-being is being utilized. To this end, this study explores the connections between technology-enhanced feedback, motivation, competence and the relationship with teachers. A nationally representative sample of pupils undertaking Finnish basic education (N=2031) was analyzed using latent profile analysis. Seven patterns for receiving technology-enhanced feedback were identified. Most girls (80%) and boys (55%) belonged to groups receiving mainly positive feedback in the form of teacher praise, which was connected to the highest scores in all measured indicators. Although the results indicate teachers’ efforts to encourage pupils through technology-enhanced feedback, we also identified profiles in which pupils (up to 30%) repeatedly received negative feedback related to behavior problems or forgotten matters, as well as profiles in which pupils (5%) reported that they never received any technology-enhanced feedback at all. Pupils who did not receive any feedback reported the lowest values in all scales. The relationship with teachers was particularly weak for pupils receiving negative feedback or no feedback. The results indicate that current technology-enhanced feedback practices do not fully meet pedagogical knowledge concerning efficient feedback.
Keywords: technology-enhanced feedback, motivation, competence, academic well-being
Research Article
Myriah T. Miller, Jill Olthouse
CONT ED TECHNOLOGY, Volume 4, Issue 1, pp. 66-80
ABSTRACT
This comparative study identified the differences between gifted children’s offline and online peer feedback within a summer talented writer’s workshop. Researchers analyzed ten students’ writings for degrees of critical thinking evident in their feedback. Online feedback included students’ writings in social writing sites Storybird.com and KidBlog. Offline feedback was submitted on a teacher designed rubric, and then incorporated into a revised manuscript using Microsoft Word. Critical thinking was defined as the three upper tiers of Bloom’s Taxonomy: analysis, and evaluation, and synthesis. Each comment in students' online and offline feedback was coded according to one of the levels of Bloom's Taxonomy. In addition, interpretative summaries were written describing how students used feedback within each category. Results indicated that critical thinking (specifically analysis and evaluation) was more evident in the responses that were structured opposed to those that were in the social media contexts. There was also evidence of an increased amount of informal dialogue in the online feedback opposed to the structured feedback. Online writing technologies are seen to be most successful when teachers' expectations for critical thinking and students' desire for informal positive feedback are combined; this success depends on the presence of a skilled teacher and supportive peers, rather than on the presence of a specific technology tool.
Keywords: Critical thinking, Educational technology, Peer feedback, Bloom’s Taxonomy, Gifted Students, Social Media, Writing
Research Article
Vibha Chawla, Praveen Thukral
CONT ED TECHNOLOGY, Volume 2, Issue 1, pp. 77-87
ABSTRACT
This study is an attempt to evaluate the effects of student feedback in developing teaching competence among student teachers. The study was conducted on ten student-teachers of one of the reputed colleges of Panjab University using single-group pretest-posttest design. The efficiency of employing all the selected skills has been calculated by using observation schedule cum rating scale for each skill. The efficiency has been found to be greater than 83% in case of all the student-teachers trained through student feedback. The coefficient of correlation between Efficiency of Using Five Selected Teaching Skills and Posttest Baroda General Teaching Competence Scale Score has been found to be 0.260. Also, 10% of the student-teachers move from average to high performance category on Stanine scale. In brief, student feedback has been found to be effective in improving the general teaching competence of student-teachers.
Keywords: Student feedback, Teaching competence, Teaching skills, Microteaching