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Levels of Science Identity, Belonging and Experiences of Discrimination for Commencing Science Students at an Australian University
Get PDFA key step in achieving gender equality in the science, technology, engineering, and mathematics (STEM) workforce is recruiting more women into undergraduate STEM degrees. Some disciplines, such as biology, have been more successful at this than others. Yet, gender issues at university still exist in these science disciplines, which may be deterring women from remaining in this career pathway. This case study at an Australian university explored known risk factors for attrition by surveying 215 first-year undergraduate science students. It also investigated how these factors differ for students in the ‘gender-balanced’ and ‘gender-unbalanced’ science fields. Findings showed that female students in both the ‘gender-balanced’ and ‘gender-unbalanced’ science fields begin university with low levels of belonging, and encounter experiences of discrimination early on. These findings highlight potential risk factors for attrition for incoming Australian science undergraduates, and some potential challenges tertiary educators need to be aware of within their first-year classrooms
Preparing for the future job market: Invent your own client report
Get PDFNo matter where students end up after university, an essential proficiency is the ability to communicate with ‘clients’, whether their employer, a business contact, or the research community. Regardless how the job market changes, students need to be able to convince stakeholders of the importance of their work. How can authentic, client-focused assessments in data science help students to gain this vital skill?
Our study focuses on data from DATA1001 (Foundations of Data Science) at The University of Sydney, which has a large, diverse cohort of more than 2000 students per year. To prepare students for the future job market, the capstone data project takes the form of a “client report”, in which students choose one of three complex data sets, and then pose their own research questions for a chosen client. We investigate how the students approach the open-ended nature of this task, and the types of questions that they ask. Interesting results emerge in terms of the global and ethical nature of the chosen questions, and the nature of the clients, real or imagined. We also consider what type of statistical analysis was needed for such an open-ended investigation and how it aligns with learning outcomes
Self-Regulation Learning Theory: The effects of metacognitive scaffolding on student metacognition and motivation
Get PDFAustralian educational institutions are currently facing a decline in upper secondary science course enrolments and perform one-and-three-quarter school years lower in science compared to higher performing countries (Australian Council for Educational Research [ACER], 2018; Kennedy et al., 2014). Furthermore, increased access to information results in new demands of actively acquiring and adapting existing knowledge more rapidly, which increases the responsibility of educational institutions to promote the development of proactive learners, who practice “self-regulated learning” (OECD, 2003). The Self-Regulated Learning Theory (SRLT) argues that successful learners rely on internal regulatory skills and become self-sufficient through refining and regulating their cognitive, motivational, and metacognitive knowledge (Schraw et al., 2006).
This study investigates successful learning through the SLRT, specifically focusing on Metacognition and Motivation knowledge and practices of senior secondary chemistry students in NSW. Throughout the course of a term, students engage with various data collection instruments (pre- and post- Metacognition and Motivation questionnaire, integrated Metacognitive Scaffolding Interventions in the form of reflection tasks, and post-intervention focus group interviews).
This presentation will outline how Metacognitive Regulation and Motivation change, or stay the same, during a term. It will also give insight into student perceptions of their metacognitive practices and motivations. Finally, it will compare this knowledge with academic performance to consider the influences of cognition on the self-regulation of chemistry students.
REFERENCES
Australian Council for Educational Research. (2018). PISA 2018: Australian student performance in long-term decline. Australian Council for Educational Research - ACER. https://www.acer.org/au/discover/article/pisa-2018-australian-student-performance-in-long-term-decline
Kennedy, J., Lyons, T., & Quinn, F. (2014). The continuing decline of science and mathematics enrolments in Australian high schools. Teaching Science, 60(2), 34–46.
OECD. (2003). Learners for Life: Student Approaches to Learning: Results from PISA 2000. Organisation for Economic Co-operation and Development. https://www.oecd-ilibrary.org/education/learners-for-life-student-approaches-to-learning_9789264103917-en
Schraw, G., Crippen, K. J., & Hartley, K. (2006). Promoting Self-Regulation in Science Education: Metacognition as Part of a Broader Perspective on Learning. Research in Science Education, 36(1), 111–139. https://doi.org/10.1007/s11165-005-3917-
Assessing the quality of peer feedback in an online peer learning community
Get PDFA goal of higher education is the development of students’ evaluative judgment, that is, the capacity to make judgements of the quality of work done by oneself and others. Over-reliance on judgements of teachers, for example by focusing on grades, can inhibit students developing this ability. Peer review is one approach that can develop evaluative judgement but an issue that may prevent its implementation is the perceived quality of peer feedback. We used an online platform, PeerWise, in a second year genetics course to investigate the quality of peer feedback and whether evaluative judgment was evident. PeerWise enables students to write, comment on, answer and rate multiple choice questions. We found it necessary to allocate some marks as an incentive for participation but 5% of the course grade resulted in high engagement with minimal intervention from the convenor. This set-up allowed students to make and share judgements anonymously in a low-stakes context. Maximum marks were awarded for writing four accurate questions, covering at least three of the four content modules, and submitting four meaningful comments. This resulted in 959 questions and 1529 comments from 248 students. A qualitative analysis of all comments led to the identification of five criteria used to assess questions: knowledge, clarity, complexity, engagement and explanation. Students demonstrated the ability to make complex and reasonable judgements about question quality invoking multiple criteria. They made constructive suggestions for improvement and reflected on their own learning, consistent with the development of evaluative judgement. 
Charles-Valentin Alkan (1813-1888): Marrano Musical Composer
Get PDFCharles-Valentin Alkan (1813-1888): Marrano Musical Compose