Demonstrator training needs to be active and focused on personalized student learning in bioscience teaching laboratories

Raheela Awais,Elliott Stollar

FEBS OPEN BIO(2021)

引用 1|浏览1
暂无评分
摘要
Demonstrators spend significant time with students on a weekly basis in instructional laboratories and are well poised to offer students meaningful learning. Most often, effective demonstrator training is neglected due to time and resource restraints and it is clear more attention is needed. We hypothesized that students' learning experience in laboratories would improve if demonstrators were well trained particularly across three overlapping learning domains: subject-specific knowledge (cognitive and psychomotor), problem solving (cognitive) and group management including personalized student learning strategies (affective). We assessed both students and demonstrators on the impact of this extensive demonstrator training in 1st- and 2nd-year bioscience practical courses over two years. The results show that all students rated the demonstrators' performance higher after the extensive training. Students from both years valued the provision of problem-solving skills; however, 1st-year students placed greater value on the demonstrator's ability to address student inclusivity, whereas 2nd-year students preferred the provision of strong subject knowledge. Interestingly, demonstrators' own perception of their teaching ability was different from student feedback on their performance, which may be due to lack of reflective practice. We propose a multimodal training framework that includes inclusivity/approachability and reflection as an integral part of training. This study further suggests that demonstrator training needs to be tailored to the changing needs of students as they progress through the different levels of their degree. Our proposed framework is particularly relevant to the current pandemic which has affected young people's mental health, confidence and openness to new experiences.
更多
查看译文
关键词
Demonstrators, expectations, first- and second-year undergraduates, laboratory, training, student satisfaction
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要