Dr. Blake Cutler

Instructor

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Biography

Blake Cutler is a PhD candidate in the School of Education at Monash University, focusing on the critical intersection of research use and educational practice. His work challenges oversimplified binaries in research-informed practices and addresses the complexities of professional practice supported by a diverse evidence base. Cutler is particularly interested in enhancing teachers' capabilities in discerning and implementing research-based decisions effectively within their contexts. He employs a variety of qualitative and quantitative research methods, including autoethnography and structural equation modeling, to advance his research agenda. In collaboration with the Monash Q Lab and Brisbane Catholic Education, Blake is co-leading initiatives aimed at fostering research-informed improvement in educational settings. His previous involvement in the Centre for Youth Policy and Education Practice has equipped him with the expertise to address the pedagogical challenges faced by diverse youth. Beyond his research, Blake contributes to teaching in courses such as Evidence-Based Action and Approaches to Teaching and Learning.

Research Interests

Experience

Sessional Academic

2019-01-01 — Present

Monash University • Melbourne, VIC

Engaged in sessional teaching and research activities in the School of Education.

Awards

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Dean's Award for Excellence in Research Engagement Impact

2023-08-02
#

Australian Government Research Training Program Scholarship

2022-01-01

Requirements for Monash University

Master Program
Requirements
GPA Requirement
Required:3
IELTS
Listening
Required:6
Reading
Required:6
Writing
Required:6
Speaking
Required:6
Overall
Required:6.5
TOEFL
Listening
Required:12
Reading
Required:13
Writing
Required:21
Speaking
Required:18
Total
Required:79
Prerequisites
Bachelor degree (or equivalent) in a related field
Application Checklist
  • Academic Transcripts
  • Proof of English Proficiency
  • Curriculum Vitae
  • Copy of Passport
Specialization Notes

Requirements are standardized across the Faculty of Information Technology for most Master's programs including Computer Science and Data Science.