Archive: Curriculum

Blog: 11 Important Things to Know About Evaluating Curriculum Development Projects*

Posted on July 24, 2019 by  in Blog ()

Professor of Instructional Technology, Bloomsburg University of Pennsylvania

Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Curriculum development projects are designed to create new content or present content to students in a new format with new activities or approaches. The following are important things to know about evaluating curriculum development projects.

1.     Understand the underlying model, pedagogy, and process used to develop the curriculum. There are several curriculum development models, including the DACUM model (Developing a Curriculum), the Backward Design Method, and the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model of instructional design. Whatever approach is used, make sure you understand its methodology and underlying philosophy so that these can help guide the evaluation.

2.     Establish a baseline. If possible, establish what student performance was before the curriculum was available, to assess the level of change or increased learning created as a result of the new curriculum. This could involve data on student grades or performance from the year before the new curriculum is introduced or data on job performance or another indicator.

3.     Clearly identify the outcomes expected of the curriculum. What should students know or be able to do when they have completed the curriculum? Take the time to understand the desired outcomes and how the curriculum content, activities, and approach support those outcomes. The outcomes should be directly linked to the project goals and objectives. Look for possible disconnects or gaps.

4.     Employ a pre/post test design. One method to establish that learning has occurred is to measure student knowledge of a subject before and after the curriculum is introduced. If you are comparing two curriculums, you may want to consider using one group as a control group that would not use the new curriculum and comparing the performance of the two groups in a pre/post test design.

5.     Employ content analysis techniques. Content analysis is the process of analyzing documents (student guides, instructor guides, online content, videos, and other materials) to determine the type of content, frequency of content, and internal coherence (consistency of different elements of the curriculum) and external coherence (interpretation in the curriculum fits the theories accepted in and outside the discipline).

6.     Participate in the activities. One effective method for helping evaluators understand the impact of activities and exercises is to participate in them. This helps determine the quality of the instructions, the level of engagement, and the learning outcomes that result from the activities.

7.     Ensure assessment items match instructional objectives. Assessment of student progress is typically measured through written tests. To ensure written tests assess the student’s grasp of the course objectives and curriculum, match the assessment items to the instructional objectives. Create a chart to match objectives to assessment items to ensure all the objectives are assessed and that all assessment items are pertinent to the curriculum.

8.     Review guidance and instruction provided to teachers/facilitators in guides. Determine if the materials are properly matched across the instructor guide, student manual, slides, and in-class activities. Determine if the instructions are clear and complete and that the activities are feasible.

9.     Interview students, faculty, and, possibly, workforce representatives. Faculty can provide insights into the usefulness and effectiveness of the materials, and students can provide input on level of engagement, learning effort, and overall impression of the curriculum. If the curriculum is tied to a technician profession, involve industry representatives in reviewing and examining the curriculum. This should be done as part of the development process, but if it is not, consider having a representative review the curriculum for alignment with industry expectations.

10.  Use Kirkpatrick’s four levels of evaluation. A highly effective model for evaluation of curriculum is called the Kirkpatrick Model. The levels in the model measure initial learner reactions, knowledge gained from the instruction, behavioral changes that might result from the instruction, and overall impact on the organization, field, or students.

11.  Pilot the instruction. Conduct pilot sessions as part of the formative evaluation to ensure that the instruction functions as designed. After the pilot, collect end-of-day reaction sheets/tools and trainer observations of learners. Having an end-of-program product—such as an action-planning tool to implement changes around curriculum focus issue(s)—is also useful.

RESOURCES

For detailed discussion of content analysis, see chapter 9 of Gall, M. D., Gall, J. P, & Borg, W. R. (2007). Educational research: An introduction (8th ed.). Boston: Pearson.

DACUM Job Analysis Process: https://s3.amazonaws.com/static.nicic.gov/Library/010699.pdf

Backward Design Method: https://educationaltechnology.net/wp-content/uploads/2016/01/backward-design.pdf

ADDIE Model: http://www.nwlink.com/~donclark/history_isd/addie.html

Kirkpatrick Model: http://www.nwlink.com/~donclark/hrd/isd/kirkpatrick.html

 

* This blog is a reprint of a conference handout from an EvaluATE workshop at the 2011 Advanced Technological Education PI Conference.

Blog: Logic Models for Curriculum Evaluation

Posted on June 7, 2017 by , in Blog ()
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Rachel Tripathy Linlin Li
Research Associate, WestEd Senior Research Associate, WestEd

At the STEM Program at WestEd, we are in the third year of an evaluation of an innovative, hands-on STEM curriculum. Learning by Making is a two-year high school STEM course that integrates computer programming and engineering design practices with topics in earth/environmental science and biology. Experts in the areas of physics, biology, environmental science, and computer engineering at Sonoma State University (SSU) developed the curriculum by integrating computer software with custom-designed experiment set-ups and electronics to create inquiry-based lessons. Throughout this project-based course, students apply mathematics, computational thinking, and the Next Generation Science Standards (NGSS) Scientific and Engineering Design Practices to ask questions about the world around them, and seek the answers. Learning by Making is currently being implemented in rural California schools, with a specific effort being made to enroll girls and students from minority backgrounds, who are currently underrepresented in STEM fields. You can listen to students and teachers discussing the Learning by Making curriculum here.

Using a Logic Model to Drive Evaluation Design

We derived our evaluation design from the project’s logic model. A logic model is a structured description of how a specific program achieves an intended learning outcome. The purpose of the logic model is to precisely describe the mechanisms behind the program’s effects. Our approach to the Learning by Making logic model is a variant on the five-column logic format that describes the inputs, activities, outputs, outcomes, and impacts of a program (W.K. Kellogg Foundation, 2014).

Learning by Making Logic Model

Click image to view enlarge

Logic models are read as a series of conditionals. If the inputs exist, then the activities can occur. If the activities do occur, then the outputs should occur, and so on. Our evaluation of the Learning by Making curriculum centers on the connections indicated by the orange arrows connecting outputs to outcomes in the logic model above. These connections break down into two primary areas for evaluation: 1) teacher professional development, and 2) classroom implementation of Learning by Making. The questions that correlate with the orange arrows above can be summarized as:

  • Are the professional development (PD) opportunities and resources for the teachers increasing teacher competence in delivering a computational thinking-based STEM curriculum? Does Learning by Making PD increase teachers’ use of computational thinking and project-based instruction in the classroom?
  • Does the classroom implementation of Learning by Making increase teachers’ use of computational thinking and project-based instruction in the classroom? Does classroom implementation promote computational thinking and project-based learning? Do students show an increased interest in STEM subjects?

Without effective teacher PD or classroom implementation, the logic model “breaks,” making it unlikely that the desired outcomes will be observed. To answer our questions about outcomes related to teacher PD, we used comprehensive teacher surveys, observations, bi-monthly teacher logs, and focus groups. To answer our questions about outcomes related to classroom implementation, we used student surveys and assessments, classroom observations, teacher interviews, and student focus groups. SSU used our findings to revise both the teacher PD resources and the curriculum itself to better situate these two components to produce the outcomes intended. By deriving our evaluation design from a clear and targeted logic model, we succeeded in providing actionable feedback to SSU aimed at keeping Learning by Making on track to achieve its goals.