Data Driven Assessment

What are some examples of data-driven assessment techniques?

• Multiple choice questions, surveys, quizzes, and performance analytics
• Brainstorming and ideation sessions
• Observations and case studies
• Interviews and focus groups

How can data-driven assessment techniques enhance teaching and learning outcomes?

• By limiting the flexibility of teaching methods
• By increasing the workload for both teachers and students
• By creating more confusion and frustration for students
• By providing valuable insights into student progress and areas for improvement, allowing teachers to tailor their instruction to meet the specific needs of their students.

Why is reflection important in the learning process?

• It helps students connect new concepts to their existing understanding

• It encourages critical thinking and metacognition

• It allows for identification of areas that require further focus

• All of the above

Data-driven assessment techniques rely on collecting and analyzing (a)   to make informed decisions about student learning.

Which one is NOT a technique associated with data driven assessment ?

• Formative assessment

• Summative assessment

• Interview-based assessment
• Bench mark assessment

4. True or False:
   Data-driven assessment techniques are primarily focused on evaluating the final outcomes of student performance.

• True

• False

Data-driven assessment techniques can help identify students' (a)   and inform instructional strategies.

How would you rate your experience?

• Excellent

• Good

• Average

• Needs Improvement

1. Do you have any suggestions or observations you would like to share:

What do you aim to achieve at the end of this program?