Data-Driven Instruction

2018 ◽  
pp. 23-87
Keyword(s):  
Data Driven ◽  
Data Driven Instruction

L2 Chinese learners’ pragmatic developmental patterns in data-driven instruction and computer-mediated communication (CMC)

2019 ◽  
Vol 1 (2) ◽  
pp. 154-183 ◽  
Author(s):  
Qiong Li
Keyword(s):  
Computer Mediated Communication ◽  
Data Driven ◽  
Pragmatic Competence ◽  
Mediated Communication ◽  
Final Particle ◽  
Developmental Patterns ◽  
Data Driven Instruction ◽  
Computer Mediated ◽  
Chinese Learners ◽  
L2 Chinese

Abstract This study examined second language (L2) Chinese learners’ developmental patterns of pragmatic competence in two computer-mediated communication (CMC) conditions: (1) CMC with data-driven instruction embedded in the course of CMC and (2) CMC without data-driven instruction. Learners’ pragmatic competence was operationalized as their ability to use a Chinese sentence final particle (SFP) ne during CMC with a native speaker partner. The study investigated: (1) whether learners (as a group) developed their use of ne over time in the two CMC conditions, and (2) how individual learners changed their use of ne (if any) in the two conditions. The quantitative analysis (token and type frequency of ne) revealed that CMC itself did not promote learners’ use of ne. However, it promoted learners’ production of ne when data-driven instruction was incorporated into CMC. Supporting the quantitative findings, the qualitative analysis showed that one learner in the CMC with data-driven instruction outperformed his counterpart in the CMC without data-driven instruction group in the diverse use of ne.

scholarly journals Blended Learning Immersion Teacher Education: Evidence-Based Practices and Data-Driven Instruction

2021 ◽  
pp. 1-30
Author(s):  
T.J. Ó Ceallaigh ◽  
Keyword(s):  
Blended Learning ◽  
Teacher Development ◽  
Teacher Educators ◽  
Lessons Learned ◽  
Data Driven ◽  
Evidence Based ◽  
Learning Approaches ◽  
Evidence Based Practices ◽  
Data Driven Instruction ◽  
Policy Practice

The practice of blending different learning approaches and strategies in higher-level education is not new, yet our understanding of how to design the most effective and efficient blend remains incomplete. Challenges are further compounded when students are not fully proficient in the language of instruction. However, teacher educators learn about teaching through learning about student learning. Evidence-based practices and data-driven instruction create conditions for success in blended learning design and implementation. This chapter reviews the impact of a blended learning professional development (PD) initiative, with a dual focus on language and content, on Irish-medium immersion (IMI) teacher development. Findings provide unique insights in relation to the effectiveness of a blended learning PD experience as indicated by student motivation, autonomy and success. Linguistic and pedagogical capacity were fostered and community cultivated. Lessons learned and tutor reflections are also shared in an attempt to advance learning in the field and to cultivate future innovation in policy, practice and possibilities.

Data Do Not Drive Themselves

2018 ◽  
Vol 111 (7) ◽  
pp. 535-539 ◽  
Author(s):  
Rob Wieman
Keyword(s):  
High School ◽  
Mathematics Teacher ◽  
Assistant Principal ◽  
Data Driven ◽  
Student Work ◽  
Data Driven Instruction ◽  
Math Teachers ◽  
High School Math ◽  
Common Assessments ◽  
Improve Instruction

Several years ago, I was working with a group of high school math teachers. Their assistant principal was impressed with their practice of sharing data from common assessments, assuming that they used these data to drive instruction. However, when I asked the teachers which data they used when teaching, they said that student work and questions during class were much more valuable. Apparently, people may interpret “data-driven instruction” differently. As a mathematics teacher, what data can you collect, and how can you use those data to improve instruction?

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