Year
2024Credit points
10Campus offering
Prerequisites
Nil
Unit rationale, description and aim
Educational policymakers, school leaders, and parents increasingly ask for evidence that teaching and learning programs are effective in terms of learning outcomes and associated costs. What constitutes evidence varies widely depending on the purpose – for example, a decline in the Programme for International Student Assessment (PISA) rankings is enough evidence for some to suggest that large scale changes in how schools operate are needed, whereas others consider randomized controlled trials as necessary evidence before accepting new programs. For teachers attempting to make decisions about the teaching and learning programs to implement in the classroom to meet the diverse needs of all children, the request for evidence can lead to frustration and confusion due to limited and sometimes conflicting research available on many of the programs. At the same time, reliance on familiar old programs that fall short of being evidence-based or on untested new “flavour-of-the-month” programs aggressively marketed to teachers often result in unrealistic expectations and adverse effects due to the wasted time and resources.
This unit focuses on the knowledge teachers need to accurately evaluate teaching and learning programs both prior to and during the implementation. This includes analysing (1) what constitutes evidence, (2) what is sufficient evidence for an existing program, (3) how to continuously assess the effectiveness of the program they choose to implement, and (4) how to combine all the information to establish decision making practices that are continuously informed by both internal and external data. The specific focus will be on evidence for literacy programs.
The aim of this unit is to equip students with necessary knowledge, skills and attitudes required for selecting effective teaching and learning programs in general and literacy programs in specific, continuously evaluating their effectiveness for all students, and to lead their schools in the use of data-based decision making to allow constant evaluation and modification of teaching and learning programs aimed at maximizing the literacy gains for all students.
Learning outcomes
To successfully complete this unit you will be able to demonstrate you have achieved the learning outcomes (LO) detailed in the below table.
Each outcome is informed by a number of graduate capabilities (GC) to ensure your work in this, and every unit, is part of a larger goal of graduating from ACU with the attributes of insight, empathy, imagination and impact.
Explore the graduate capabilities.
| Learning Outcome Number | Learning Outcome Description |
|---|---|
| LO1 | Demonstrate ability to locate, organise, analyse, synthesise and evaluate evidence for literacy teaching and learning programs (APST Lead 1.5, 2.1, 2.5) |
| LO2 | Analyse and reflect on the adequacy of assessment and other data currently available in their school or professional context (APST HA 1.5, Lead 1.5) |
| LO3 | Reflect critically on the evidence currently used in schools to select and justify use of teaching and learning programs (APST Lead 3.6, 5.1) |
| LO4 | Understand the tenants and practices of data-driven decision making (DDDM) as applied to literacy instruction by demonstrating knowledge of the purpose, relevant data sources, analyses, interpretations and implications, and associated actions consistent with DDDM (APST HA 1.5, 5.4, Lead 1.5, 5.4) |
| LO5 | Apply understanding of evidence, evidence-based programming and data-informed decision making to implement quality data-informed decision-making practices in literacy (APST HA 5.4, Lead 3.2, 5.4) |
AUSTRALIAN PROFESSIONAL STANDARDS FOR TEACHERS - HIGHLY ACCOMPLISHED
On successful completion of this unit, students should have gained evidence towards the following standards:
1.5 Differentiate teaching to meet the specific learning needs of students across the full range of abilities Evaluate learning and teaching programs, using student assessment data, that are differentiated for the specific learning needs of students across the full range of abilities. |
5.4 Interpret student data. Work with colleagues to use data from internal and external student assessments for evaluating learning and teaching, identifying interventions and modifying teaching practice. |
AUSTRALIAN PROFESSIONAL STANDARDS FOR TEACHERS - LEAD
On successful completion of this unit, students should have gained evidence towards the following standards:
1.5 Differentiate teaching to meet the specific learning needs of students across the full range of abilities Lead colleagues to evaluate the effectiveness of learning and teaching programs differentiated for the specific learning needs of students across the full range of abilities. |
2.1 Content and teaching strategies of the teaching area Lead initiatives within the school to evaluate and improve knowledge of content and teaching strategies and demonstrate exemplary teaching of subjects using effective, research-based learning and teaching programs |
2.5 Literacy and numeracy strategies Monitor and evaluate the implementation of teaching strategies within the school to improve students’ achievement in literacy and numeracy using research-based knowledge and student data |
3.2 Plan, structure and sequence learning programs Exhibit exemplary practice and lead colleagues to plan, implement and review the effectiveness of their learning and teaching programs to develop students’ knowledge, understanding and skills. |
3.6 Evaluate and improve teaching programs Conduct regular reviews of teaching and learning programs using multiple sources of evidence including: student assessment data, curriculum documents, teaching practices and feedback from parents/carers, students and colleagues. |
5.1 Assess student learning Evaluate school assessment policies and strategies to support colleagues with: using assessment data to diagnose learning needs, complying with curriculum, system and/or school assessment requirements and using a range of assessment strategies. |
5.4 Interpret student data Co-ordinate student performance and program evaluation using internal and external student assessment data to improve teaching practice. |
Content
This unit comprises two modules.
In Module 1, students will examine what constitutes evidence according to two influential evaluators of teaching and learning programs in North America: What Works Clearinghouse (WWC) operated by Institute of Educational Research in US, and Council for Exceptional Children (CEC), the largest professional organization of special educators in North America.
Both guidelines agree that “instructional techniques with meaningful research supporting their effectiveness” (Cook & Cook, 2013, p. 72) form the basis of evidence-based practice but differ in their interpretation of what research is considered meaningful. Module 1 concludes with a reflection of how these guidelines apply to education research and practice in Australia in general, and to selection and use of teaching and learning programs in individual schools in particular. To meet this latter goal, students will learn to locate, organise, analyse, synthesise and evaluate evidence for literacy teaching and learning programs currently used in their schools.
In Module 2, students analyse the principles and different practices of data-informed decision making. They will examine different ways to continuously collect evidence to establish the effectiveness of their own practice. Students will complete the Using Data-Based Individualization to Intensify Instruction challenge (https://iris.peabody.vanderbilt.edu/module/dbi1/challenge/#content). Finally, they will combine all the information to create a plan for sustainable decision-making practices that are continuously informed by both internal and external data.
Learning and teaching strategy and rationale
The unit is offered in multi-mode format and supported by a unit learning management site (LMS). Students will engage in an experiential learning cycle of conceptual learning and inquiry; engagement with existing research; active experimentation in their classrooms; and collecting and evaluating evidence. Engagement for learning is the key driver in the delivery of this unit. The unit will facilitate active participation in pedagogical approaches that demonstrate alignment of teaching, learning and assessment and incorporate:
- Online digital resources, including reference readings, database and document searches, and recorded lectures from experts;
- Online or face-to-face small group collaborative learning to foster reflective practice following the personal analysis, evaluation and synthesis of relevant literature and current practices in different schools;
- Online forum and chat tools to build a community of learners; and
- Problem-based learning sessions to develop necessary skills and analyse and apply learning to school case studies.
This is a 10-credit point unit and has been designed to ensure that the time needed to complete the required volume of learning to the requisite standard is approximately 150 hours in total across the semester.
Mode of delivery: This unit will be offered in one or more of modes of delivery described below, chosen with the aim of providing flexible delivery of academic content.
- On Campus: Most learning activities or classes are delivered at a scheduled time, on campus, to enable in-person interactions. Activities will appear in a student’s timetable.
- Intensive: In an intensive mode, students require face-to-face attendance on weekends or any block of time determined by the school. Students will have face-to-face interactions with lecturer(s) to further their achievement of the learning outcomes. This unit is structured with required upfront preparation before workshops. The online learning platforms used in this unit provide multiple forms of preparatory and practice opportunities for you students to prepare and revise.
- Multi-mode: Learning activities are delivered through a planned mix of online and in-person classes, which may include full-day sessions and/or placements, to enable interaction. Activities that require attendance will appear in a student’s timetable.
- Online unscheduled: Learning activities are accessible anytime, anywhere. These units are normally delivered fully online and will not appear in a student’s timetable.
- Online scheduled: All learning activities are held online, at scheduled times, and will require some attendance to enable online interaction. Activities will appear in a student’s timetable.
Assessment strategy and rationale
In order to successfully complete this unit, students need to complete and submit two graded assessment tasks. The two tasks offer students opportunities to demonstrate knowledge of how evidence is conceptualised in educational research, how it is compiled to assess whether there are sufficient evidence to support practices, what evidence can and should be collected locally to establish that the practices are effective, and how internal and external evidence are combined to support continuous evidence-informed decision making.
The first task (50%) is related to the core modules and requires students to demonstrate their understanding of issues associated with evidence-based practice and data-informed decision making. The second task (50%) is related to knowledge of evidence-based instruction and assessments, and requires the students to apply their knowledge and skills to an existing teaching context.
Overview of assessments
| Brief Description of Kind and Purpose of Assessment Tasks | Weighting | Learning Outcomes |
|---|---|---|
Assessment Task 1 – Written assignment Analyse current understanding of evidence and evidence-based practice in educational research and construct criteria for evaluating programs that (1) are supported by existing approaches, and (2) can guide differentiated instruction and assessment of students. | 50% | LO1, LO2, LO3, LO4 |
Assessment Task 2 -Written assignment Compose a plan for a data-based decision making that can be implemented in your school or professional setting to guide all program selection and evaluation decisions. | 50% | LO4, LO5 |
Representative texts and references
Arden, S. V., & Pentimonti, J. M. (2017). Data-Based Decision Making in Multi-Tiered Systems of Support: Principles, Practices, Tips, & Tools. Perspectives on Language and Literacy, 43(4), 19–23.
Arden, S. V., & Benz, S. (2018). The Science of RTI Implementation: The How and What of Building Multi-tiered Systems of Support. Perspectives on Language and Literacy, 44(4), 21–25.
Brown, J., Skow, K., & the IRIS Center. (2009). RTI: Data-based decision making. Retrieved from https://iris.peabody.vanderbilt. edu/wp-content/uploads/pdf_case_studies/ics_rtidm.pdf
Cook, B. G., & Cook, L. (2016). Research designs and special education research: Different designs address different questions. Learning Disabilities Research & Practice, 31, 190-198.
Cook, B. G., & Cook, S. C. (2013). Unraveling evidence-based practices in special education.The Journal of Special Education, 47, 71-82.
Cook, B. G., Tankersley, M., Cook, L., & Landrum, T. J. (2008). Evidence-based practices in special education: Some practical considerations. Intervention in School and Clinic, 44, 69-75.
Council for Exceptional Children. (2014). Council for Exceptional Children standards for evidence-based practices in special education. https://www.cec.sped.org/~/media/Files/Standards/Evidence%20based%20Practices%20and%20Practice/EBP%20FINAL.pdf
Gummer, E. S., & Mandinach, E. B. (2015). Building a conceptual framework for data literacy. Teachers College Record, 117(4), 1-22.
Kearns, D. M., (August, 2016). Student progress monitoring tool for data collection and graphing [computer software] Washington, DC: U.S. Department of Education, Office of Special Education Programs, National Center on Intensive Intervention.
Marx, T., Peterson, A., & Arden, S. (2020). Going virtual: Considerations for adjusting data-based individualization implementation in response to COVID-19. National Center on Intensive Intervention. https://intensiveintervention.org/sites/default/files/DBI_Virtually_508.pdf
Mesibov, G. B., & Shea, V. (2011). Evidence-based practices and autism. Autism, 15, 114-133.
Slavin, R. E. (2002). Evidence-based education policies: Transforming educational practice and research. Educational researcher, 31, 15-21.
Torgerson, C. J., Torgerson, D. J., & Taylor, C. A. (2015). Randomized Controlled Trials. In K. E. Newcomer, H. P. Hatry, & J. S. Wholey (eds.) Handbook of Practical Program Evaluation (s. 158-176). Hoboken, NJ: Wiley.
What Works Clearinghouse. (2008). What Works Clearinghouse evidence standards for reviewing studies, version 1.0. Available at http://files.eric.ed.gov/fulltext/ED511668.pdf