Geoff Woolcott, PhD Associate Professor of Mathematics and Science - PowerPoint PPT Presentation

Geoff Woolcott, PhD Associate Professor of Mathematics and Science Education School of Education Southern Cross University AUSTRALIA

find the specific DNA sequence of target species Compare DNA sequences from related species http://susanspiritusgallery.com http://wwwen.wikipedia.org http://www.artificiallagoon.com

Cognitive Load Theory based in modern cognitive psychology A scientific view based in modern integrative biology http://froemming.wordpress.com http://www.enrichmentcorner.com. http://jmrc.arts.unsw.edu.au au

Information and information processing All structures can connect with the environment through information pathways or systems of connectivity. The changes in such information pathways can be referred to as information processing. Probabilistic models (e.g. for Computational models differentiation of signal and noise, (e.g. for describing biology, Chaitin, 2011) Shannon & Weaver, 1963) Connectionist rather than behaviourist educational theories (e.g. Sweller’s Cognitive Load Theory, 2003) Such connectivity can be interpreted in a less-used conceptualisation of information as matter and energy organised in a pattern (e.g. Bates, 2005).

A broad view of learning and memory in terms of information Learning and memory, in a very broad sense, can be said to involve three temporally- connected but separable stages in the information flow that is matter and energy connections and interactions. 1. Environmental input to or output from a structure 2. Processing of resultant information changes within the structure 3. Changes in the observed state of the structure as a result of such information processing In this broad view, information as matter and energy does NOT need to be organised in a pattern. The description of information as matter and energy, whether or not a pattern is involved, serves to identify distinct spatial entities and their learning and memory systems. My subsequent research has been built around this conceptualisation of information, which lends it self to complex systems approaches based in the natural sciences. This research, however, also embraces Tomasello’s (1999) view of cultural accumulation and ‘cultural ratcheting’ as a distinctively human characteristic enabled by the social connections made through education and teaching. I sometimes use the umbrella term of “how people learn stuff” to describe my overall research aim, but my focus is broader-how people connect with their world. Obviously learning is a key feature!

Connectivity and systems approaches (1) Examining spatiotemporal links in mathematics concept learning A two-year project supported internally by the School of Education at SCU Connectivity and systems approaches (2) It’s part of my life: Engaging university and community to enhance science and mathematics education A three-year project supported by a $1 million grant awarded by the Australian Government’s Office for Learning and Teaching (now the Department of Education and Training) Connectivity and systems approaches (3) Student-centred service integration and identification of risk factors in undergraduate university education A two-year project supported internally from SCU Connectivity and systems approaches (4) Bite size maths: Building mathematics capability of low SES students in regional/remote Australia A one-year project supported by $140,000 grant awarded by the Australian Government’s Higher Education Participation Program Connectivity and systems approaches (5) Collaborative networks, impact and sustainability

Connectivity and systems approaches (1) Examining spatiotemporal links in mathematics concept learning Network analysis (bi-modal) of inferred relationships between measurement items for a Year 3-6 individuals, based on shared outcomes/concepts

Longitudinal tracking of concept development: Inferred connectivity of the incorrect Year 6 Item 10 with items in Years 3-5. Solid lines are based on incorrect to incorrect connections and and dashed lines on incorrect to correct items. Items are indicated by filled squares with an item number. Presentation of this work at a Vancouver conference in 2014 connected me to the Spatial Reasoning Study Group (www.spatialresearch.org) organised by Prof Brent Davis (University of Calgary), working on spatial research networks.

Understanding Collaborative Research Networks - The Spatial Reasoning Study Group Figure 3. A network map representing the directed connections of citations between disciplines. The red circles represent the consensus Modal Disciplines. The blue squares represent by size the number of papers from differing disciplines that were cited in the source papers of the Modal Disciplines (2-mode greater than 100 ties with nodes weighted by degree). Darker lines show larger numbers of connections. (Arrows going from blue to red not included.)

Understanding Collaborative Research Networks The Spatial Reasoning Study Group

Using structural holes to construct collaborations – the SRSG new grant: Connecting mathematics learning through spatial reasoning . Australian Research Council Discovery Project funded through 2017-2020 ($300,000). Project partners Prof Joanne Mulligan (lead CI), Associate Professor Geoff Woolcott, Prof Michael Mitchelmore (CI) (Macquarie University) and Prof Brent Davis (PI) (University of Calgary, Canada).

Connectivity and systems approaches (2) It’s part of my life: Engaging university and community to enhance science and mathematics education Office of the Chief Scientists STEM funding program AMSPP funded through the Australian Maths and Science Australian government Office AMSPP second round projects Partnership Program (AMSPP) 2014 for Learning and Teaching Priority projects early 2013 (OLT) Inspiring Science & It’s part of my life: Engaging Evaluating and selecting STEM Mathematics Education (iSME) , university and community to Regional universities network resources: capacity building led by SCU with the University enhance science and (RUN) maths and science for teachers in rural and of Wollongong, Charles Darwin mathematics education. regional schools , led by the digital classroom: A connected University and the Australian Enhancing the Training of model for all of Australia, led UTAS, with SCU, Deakin, Edith Mathematics and Science Academy of Technological by USQ. ($1M) Cowan, USA & government and Sciences and Engineering Teachers (ETMST), a RUN industry partners. ($0.4M) (ATSE) ($1M) project led by SCU. ($1M)

The Regional Universities Network (RUN) Southern Cross University Central Queensland University Federation University Australia University of New England University of Southern Queensland University of the Sunshine Coast RUN location features • Regional - rural or peri-urban • High unemployment • Large population identifying as young indigenous • Large numbers of people identified as low socio-economic RUN university features • Diverse student representation • Large geographic coverage • External/internal course delivery • Research focus within region • Strong links with community

 Current curriculum have a genuine focus on trying to bring real world mathematics/science into the classroom, to enhance classroom studies, but the ideal mathematics/science classroom should be about the real world of mathematics/science .  We are trying to show pre-service teachers and school students that mathematics and science is ‘out there’ in the real world and that our classrooms should reflect this. The project is designed as a complex system and many of the outcomes considered as emergent. This has enabled the construction of a model that compares this project with the four other large projects in a funding scheme that accounts for 25 of Australia’s 36 universities.

The project has developed an novel Enhancement-Lesson-Reflection (ELR) process. Enhancement: Interactions with mathematics and science researchers and education specialists – in recent times through video recordings. The Enhancement involves collaborative team discussions in order to produce a plan for a teaching a ‘Teaching Lesson’ based on familiar real- world interactions, generally in a student-centred problem-solving context. Reflection: The Teaching Lesson is followed by self-reflection or collaborative reflection around affect-based critical moments in teaching – how you felt while you were teaching and why you felt that way. This serves as a non-judgemental focus for teacher improvement. We have developed protocols that can be upscaled – they are currently being utilised in course structures by all six university partners.

T he iterated ELR process can be described as design-study implementation (Penuel et al., 2016) . At the end of each ELR sequence, data collected during the process is analysed in order to determine how to re-configure the discussions/lessons in the following iteration. This allows the process to be more effective in ensuring delivery of lessons related to the project goals and strategies. The process may seem simple but it is both DISRUPTIVE and IMMERSIVE – it is both challenging and confronting since it requires a change to teaching practices.