Training for Teachers in Technology Integration

Texas Education Code 21.0452(b)(5)

Technology Integration in Curricula and Instruction with Activities Consistent with the Principles of Universal Design for Learning

Aspiring teachers in lower level education courses participate in a ‘Technology Day’. Candidates participating in this event immerse themselves in open inquiry stations with tasks based on the ISTE standards. The goal of these activities is to raise awareness of the ISTE standards and how teachers can use technology to enhance learning through meaningful and engaging ways. These activities also enable candidates to learn about newer technology, apps, digital literacy and other learning technologies being used by local districts.

Teacher candidates, while participating in Clinical Teaching during their senior year of the Educator Preparation Program, complete course work to build their capacity to integrate principles of Universal Design for Learning (UDL) into their planning to promote engagement among all students. They also complete online research-based, classroom-tested professional development modules on differentiation. Lesson plans, when appropriate, integrate the concepts of multiple intelligences, learning preferences, and Bloom’s taxonomy to qualities of UDL. Lesson reflections include discussions related to connections between UDL and differentiated instruction.

Teacher candidates participating in Clinical Teaching, must design a Modified Teacher Work Sample (TWS) that employs a range of strategies and builds on each student’s strengths, needs, and prior experiences. Through this performance assessment, teacher candidates provide credible evidence of their ability to facilitate learning by meeting the teacher standards on designing instruction for specific learning goal(s), student characteristics and needs, and learning contexts.

The candidate’s performance in integrating technology in curricula and instruction with activities consistent with the principles of UDL is assessed using a four-point rubric that includes an item for assessing the description of the planned use of technology in the lesson, the appropriateness of the technology and the contribution of the selected technology to the quality of teaching and learning.

Technology Integration with Data Analysis to Improve Students’ Academic Achievement

Teacher candidates participating in Clinical Teaching, must design a Modified Teacher Work Sample (TWS) that includes a minimum of four charts and work samples to demonstrate how he or she uses assessment data to profile student learning and communicate information about student progress and achievement.

The task requires student to analyze assessment data, including pre/post assessments and formative assessments to determine students’ progress related to the unit learning goals. Candidate use appropriate technology to create visual representations and narrative to communicate the performance of the whole class, and two individual students. To analyze the progress of the whole class, candidates use technology to create a table that shows pre- and post- assessment data on every student on every learning goal. They also create a graphic summary that shows the extent to which students made progress (from pre- to post-) toward the learning criterion that was identified for each learning goal. The narrative component this of this assessment requires the use of text-based software to summarize what the graph tells the teacher about their students' learning in the selected unit.

Candidates must also select two individuals within their class that demonstrated different levels of performance. They must explain why it is important to understand the learning of these particular students by using pre-, formative, and post- assessment data to draw conclusions about the extent to which these students attained the two learning goals. Students use appropriate technology to incorporate examples of the students’ work to support the claims and conclusions concerning the different levels of performance.

The candidate’s performance in integrating technology with data analysis is assessed using a four-point rubric that includes an item on the clarity and accuracy of the individual and whole class analysis.