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Educator Preparation Program Technology Integration and Data Analysis

Preparing Teachers to Effectively Integrate Technology into Curricula and Instruction

Instructional technology is integrated throughout our initial certification programs. Specific activities include:

  • use of social media for professional learning and the development of professional learning networks;
  • backchanneling;
  • use of technology for differentiation and Universal Design for Learning (e.g., booktalk presentation);
  • formative and summative assessments (e.g., Teacher Work Sample Assignment, Data-Driven Instruction Assignment, Teacher Observation Report);
  • creation and use of audio-video materials (e.g., Ballroom Dance Research Project, Diversity Video Project, Booktalk Presentation, Stop-Motion Video Project);
  • creation and instructional use of websites;
  • exploration of mobile and desktops apps with instructional implications (e.g., Flipgrid, Twitter, Seesaw, etc.);
  • building electronic portfolios for information sharing and assessment;
  • 3D printing (e.g., Landforms Project, Art Education Fablab Project);
  • biometric feedback (e.g., Actigraph Accelerometer and Footsteps Project);
  • demonstration the use of document cameras, interactive whiteboards, mobile interactive technologies, iPads, and Chromebooks;
  • GIS and Geoinquiry technologies.

Preparing Teachers to Effectively Use Technology to Collect, Manage, and Analyze Data to Improve Teaching and Learning

The Data-Driven Instruction assignment is composed of five data-driven lesson plans and reflections on implementing those lessons. For the assignment, candidates choose a content area, collect data, analyze the data, align to state and national standards, and design a data-driven instructional plan consisting of five lessons to address the needs of students as revealed in the data. Further, candidates implement the instructional plan, evaluate student progress, and determine the next instructional goal for students based on the results. Candidates utilize both formal and informal assessment strategies as well as Universal Design for Learning to plan and implement data-driven instruction. The results are used to improve the program as well as to improve the teaching quality of teacher candidates by measuring their ability, skills, and knowledge of data-driven lesson planning and teaching. This assessment is completed by all Early Childhood - 6th Grade and Middle Level candidates during clinical teaching.

Candidates create a chapter or mini-unit of study that shows their ability to plan for instruction, align lessons to national and state learning standards, plan and execute assessments, measure effective student learning, and adjust instruction to meet student needs. Using the foundations of the teaching methods introduced in the Secondary and All-Level Education teacher certification programs, candidates will develop a Teacher Work Sample (TWS) of an original chapter or unit plan consisting of a pre-assessment, two or more connected lessons for a chapter or mini-unit of study, at least one assessment during each lesson, and a post-assessment. The chapter/unit of study addresses three or more national standards. The chapter/mini-unit of study is led by an essential question and/or unit goals and will be taught during the mandatory two-week teaching block during clinical teaching. Candidates will analyze student data provided by summative (pre-/post-tests) and formative assessments to evaluate ongoing student learning. Candidates also reflect on the data and adjustments made while teaching to address students who have not learned the key concepts of the lesson. Finally, candidates will analyze data holistically as a class and by demographic (subpopulation) categories to determine overall student performance. This assessment is completed by all Secondary and All-Level candidates during clinical teaching.

All teacher preparation candidates complete the School Profile Project. The objectives for this assessment are to observe concepts taught in EDUC 3301 (or equivalent) in a school setting, analyze school and classroom diversity and cultural responsiveness and synthesize information to create new ideas for improving school structures for diversity. Candidates are expected to make observations regarding the school and a classroom environment, interview campus personnel, and analyze school data. Candidates will use the data to evaluate the campus and one specific classroom to assess approaches to diversity and cultural responsiveness. Candidates share recommendations based on evidence gathered in the field, provide examples to illustrate their suggestions, and explain how they will use what was learned in their future teaching assignment.