Evidence-informed collaborative inquiry for improving teaching and learning

2011 ◽  
Vol 39 (3) ◽  
pp. 247-261 ◽  
Author(s):  
Claire Sinnema ◽  
Alison Sewell ◽  
Andrea Milligan
Keyword(s):  
Teaching And Learning ◽  
Collaborative Inquiry ◽  
Improving Teaching And Learning

Turning Standardized Test Scores into a Tool for Improving Teaching and Learning

2000 ◽  
Vol 35 (3) ◽  
pp. 356-384 ◽  
Author(s):  
Jie-Qi Chen ◽  
Renee Salahuddin ◽  
Patricia Horsch ◽  
Suzanne L. Wagner
Keyword(s):  
Test Scores ◽  
Teaching And Learning ◽  
Standardized Test ◽  
Standardized Test Scores ◽  
Improving Teaching And Learning

scholarly journals Data in Schools: (Changing) Practices and Blind Spots at a Glance

2021 ◽  
Vol 6 ◽  
Author(s):  
Ulrike Krein ◽  
Mandy Schiefner-Rohs
Keyword(s):  
Teaching And Learning ◽  
Pedagogical Practices ◽  
Digital Data ◽  
Learning Assessment ◽  
Data Practices ◽  
Changing Practices ◽  
The Impact ◽  
Improving Teaching And Learning ◽  
Blind Spots

This review aims to provide a concise overview of the role of (digital) data and new data practices in schools. By focusing on the impact of data on pedagogical practices, it aims to shed light on how the everyday tasks of teachers and other pedagogical staff in schools are changing, particularly as a result of the generation and use of digital data. For this purpose, existing studies and previous theoretical debates on this topic are examined for their perspectives on data and data practices in schools. The pedagogical data practices of (improving) teaching and learning, assessment and counseling, (data-driven) decision-making, and cooperation and collaboration by “doing data” will be elaborated and discussed. Likewise, data practices that are missing from the studies are identified. We conclude with an overview of blind spots and further research needs.

Multi-Faceted Professional Development Models Designed to Enhance Teaching and Learning within Universities

2011 ◽  
pp. 412-435
Author(s):  
Donald E Scott ◽  
Shelleyann Scott
Keyword(s):  
Professional Development ◽  
Case Studies ◽  
Teaching And Learning ◽  
University Leadership ◽  
Development Models ◽  
Educational Stakeholders ◽  
Professional Networking ◽  
Integration Of Technology ◽  
Institutional Reputation ◽  
Improving Teaching And Learning

In this chapter we advocate the reconceptualisation of pedagogical focused professional development to a more flexible and systematic approach and present two technology-oriented models. This chapter is of interest to a range of educational stakeholders including university professional developers, academics, leaders, students, and support staff. Two mixed method case studies of students’ and academics’ experiences of online and blended teaching and learning informed the design of the models. These multi-faceted models are designed to promote effective pedagogically-focused professional development, the scholarship of teaching and learning, social and professional networking, and supportive university leadership all aimed at improving teaching and learning. We articulate how the integration of technology can facilitate all of these important activities. It is anticipated that, if implemented, these models will result in a more pedagogically- and techno- efficacious academy; more satisfied and successful graduates; more informed, involved, and trusted leaders; greater sustainability for programmes; and the enhancement of institutional reputation.

Educational Data Mining Techniques and Applications

2021 ◽  
pp. 234-251
Author(s):  
M. Govindarajan
Keyword(s):  
Data Mining ◽  
Learning Analytics ◽  
Teaching And Learning ◽  
At Risk Students ◽  
Educational Data Mining ◽  
Learning Needs ◽  
Institutional Performance ◽  
Clear Cut ◽  
Curriculum Renewal ◽  
Improving Teaching And Learning

Educational data mining (EDM) creates high impact in the field of academic domain. EDM is concerned with developing new methods to discover knowledge from educational and academic database and can be used for decision making in educational and academic systems. EDM is useful in many different areas including identifying at risk students, identifying priority learning needs for different groups of students, increasing graduation rates, effectively assessing institutional performance, maximizing campus resources, and optimizing subject curriculum renewal. This chapter discusses educational data mining, its applications, and techniques that have to be adopted in order to successfully employ educational data mining and learning analytics for improving teaching and learning. The techniques and applications discussed in this chapter will provide a clear-cut idea to the educational data mining researchers to carry out their work in this field.

Conversation Design in the Electronic Discussion Age

2008 ◽  
pp. 91-106 ◽  
Author(s):  
Gregory MacKinnon
Keyword(s):  
Teaching And Learning ◽  
Course Design ◽  
Collaborative Inquiry ◽  
Theoretical Framework ◽  
Future Research ◽  
Blended Courses ◽  
Inquiry Approach ◽  
Conversation Theory ◽  
Blended Course

The goal of the chapter to examine a way in which Pask’ s conversation theory (CT) can be used as a theoretical framework for designing blended courses using a collaborative inquiry approach for teaching and learning in campus-based university. This chapter comprises three parts that explains a) the constructs of CT, and their relations in regard to online collaborative inquiry, b) the four principles derived from the constructs of CT and the possible use of these principles to design a blended course, and c) how the effects of these constructs can be used to assess the effectiveness of this CT based blended course design. This chapter is concluded with the discussion and implications for course design, and future research on CT.

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