Pre-Post Test Apparatus for Knowledge Change Measurement
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Solution Overview
Problem
Current testing methods fail to effectively measure the change in knowledge gained by students after exposure to educational material, making it difficult to determine the effectiveness of the material and improvements in student knowledge.
Innovation Solution
An apparatus, system, and method that includes a storage module, pre-test module, post-test module, grading module, and summary creation module to assess changes in knowledge by comparing pre-test and post-test answers, with the ability to present educational material and generate session summaries for users and providers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single test is administered to students, then the test can be completed quickly and easily, but the test cannot determine whether the student already knew the answers or how much knowledge was gained from educational material
Solution Approach 1:
The testing process is divided into separate pre-test and post-test components. The pre-test measures baseline knowledge before educational material is presented, and the post-test measures knowledge after exposure. This segmentation allows accurate measurement of knowledge gain while maintaining testing efficiency through automated administration.
Solution Approach 2:
A pre-test is administered before the student views educational material to establish baseline knowledge. This preliminary measurement enables accurate determination of knowledge change by comparing pre-test and post-test results, solving the problem of not knowing whether students already knew the answers.
2Measurement precision
If pre-test and post-test are administered to measure knowledge change, then the effectiveness of educational material can be determined, but the testing process becomes more complex and time-consuming
Solution Approach 1:
The testing system is designed to perform multiple functions: administering pre-tests, presenting educational material, administering post-tests, automatically grading responses, and generating comprehensive reports. This multi-functionality reduces overall system complexity by integrating what would otherwise be separate processes into a single unified platform.
Solution Approach 2:
The system automatically grades student responses by comparing them to correct answers stored in the database, eliminating the need for manual grading. The system also automatically generates session summaries and knowledge change reports, reducing complexity by automating tasks that would otherwise require additional human resources and procedures.
3Loss of information
If detailed comparison of pre-test and post-test answers is performed, then insights into student learning can be provided, but the time required to process and analyze results increases
Solution Approach 1:
The system automatically compares pre-test and post-test answers, calculates knowledge change metrics, and generates detailed session summaries without requiring manual analysis. This automated processing preserves comprehensive learning insights while minimizing the time required to produce results.
Solution Approach 2:
Manual comparison and analysis of test answers is replaced with automated computer-based processing. The system uses algorithmic comparison of responses against correct answers and generates quantitative measures of knowledge gain, replacing time-consuming manual analysis with efficient automated computation.
Data Source
AI summary
An apparatus for determining a change in test results includes a storage module, a pre-test module, a post-test module, a grading module and a summary creation module. The storage module stores a plurality of questions and a correct answer to each question. The pre-test module submits a group of pre-test questions to a user and receives answers to the pre-test questions from the user (“pre-test answers”). The post-test module, in response to the user being exposed to educational material related to the pre-test questions, submits a group of post-test questions to the user and receives answers to the post-test questions from the user (“post-test answers”). The grading module compares the pre-test answers and the post-test answers. The summary creation module creates a session summary including a comparison between the pre-test answers and the post test answers. The questions and answers are submitted and received over a computer network.