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PowerPoint Presentation Building University Industry Learning and Development through Innovation and Technology Effective Assessment and Evaluation of Student Outcome Attainment VNU HCM Center for Educational Accrediation May 16, 2022 Presenters Thai Tran Program Manager for Accreditation and Quality Assurance Arizona State University Ha Mai Accreditation and Quality Assurance Specialist Arizona State University The Great Master Dr Scott Danielson Associate Professor Ira A Fulton Schools of Engi. Building University-Industry Learning and Development through Innovation and Technology VNU-HCM Center for Educational Accrediation Effective Assessment and Evaluation of Student Outcome Attainment May 16, 2022 Presenters Thai Tran Program Manager for Accreditation and Quality Assurance Arizona State University Ha Mai Accreditation and Quality Assurance Specialist Arizona State University Dr Scott Danielson Associate Professor Ira A Fulton Schools of Engineering Arizona State University The Great Master Workshop Coordinator Chau Kha BUILD-IT Coordinator Arizona State University The most important person Workshop Goals Participants will ▪ review new AUN-QA requirements related expected learning outcomes (course and program level), ▪ review basics of “measuring” student attainment of program level expected learning outcomes (AUN-QA/ABET), ▪ practice developing performance indicators for selected student outcomes, ▪ link performance indicators (PIs) to course learning outcomes, ▪ explore a specific example of assessing a PI, ▪ explore a specific example of SO assessment plan, and ▪ explore the evaluation of the assessment data for improvement Morning Session – May 16, 2022 Agenda 8:35 - 9:15 am Continuous Improvement System Requirements & AUN-QA Assessment at Program Level Version Requirement Review 9:15 - 9:30 am Selection of Program Student Outcomes to be Assessed 9:30 - 10:00 am Performance Indicators 10:00 - 11:25 am Performance Indicators and Course Learning Outcomes 11:25 - 11:30 am Application: Performance Indicator Development Afternoon Session – May 16, 2022 1:30 - 2:00 pm Review of PI Development 2:00 - 2:20 pm Assessment Planning Worksheet 2:20 - 3:20 pm Development of the Planning Worksheet 3:20 - 4:30 pm Evaluation of Assessment Data 4:30 pm Wrap-up & Thank you! Morning Session Continuous Improvement System Requirements & Performance Indicator Development May 16, 2022 HM • Expected learning outcome assessment is becoming/has become an international standard of quality Workshop Premises • In an era of accountability and transparency, continuous quality improvement is not going away • It is important for us to define anticipated student learning before someone else does it for us • Because we are going to be mandated to provide the evidence, it is critical for us to develop assessment processes that are consistent with our institutional values and honor faculty priorities Key Principle Keep the process simple and manageable! In a Continuous Quality Improvement (CQI) process, there are certain requirements for a robust CQI system that assures quality STUDENT OUTCOMES must be defined in measurable terms (performance indicators) Processes (e.g., curriculum, co-curriculum) need to be examined and aligned to understand how they contribute to the desired outcomes Data should be efficiently and systematically collected to see if the performance indicators that define the outcomes are being met Remember the second part of this worksheet? Program Score Card—All Student Outcomes Possible Approach 1: Focusing improvement actions on SOs below target All Student Outcomes Attainment Level 100% 90% 84% 75% 80% 70% 67% 79% 64% 60% 50% 40% 30% 20% This approach might have disadvantages for long-term continuous improvement efforts 10% 0% SO1 - Technical SO2 - Design Problem-solving SO3 SO4 - Analysis & SO5 - Teamwork Communication Judgment Target 75% Program Score Card—All Student Outcomes Possible Approach (highly recommended): Targeting the two lowest performing student outcomes for improvement activities All Student Outcomes Attainment Level 100% 90% 84% 75% 80% 70% 67% 79% 64% 60% 50% 40% 30% 20% 10% 0% SO1 - Technical SO2 - Design Problem-solving SO3 SO4 - Analysis & SO5 - Teamwork Communication Judgment Decision Making for Improvements ▪ An effective and simple continuous improvement process focuses on where improvements are most needed (maximize effort where it is most needed) ▪ The decision process for improvement actions can involve a number of people and processes ▪ These decisions can be approached using a structured approach that considers benefit/cost ratios Documentation of the Assessment & Evaluation Process 📂 Assessment Plan 📂 Student Outcome Attainment Data 📂 Other Input for Continuous Improvement 📂 Evaluation & Improvement Actions This is an example organization of assessment data for one cycle There are many alternatives that would be easier to use for the ABET team (not listed in order of preference): a Dropbox b Google Drive c A local server/website d Physical faculty room Documentation of the Assessment & Evaluation Process Assessment Plan Include assessment plan worksheet that contains: ▪ List of the metric(s), measure(s) or performance indicator(s) (PI) used for the assessment of each student outcome ▪ Schedule and frequency for each type of assessment as well as points of accountability (tabular format is recommended) Documentation of the Assessment & Evaluation Process Student Outcome Attainment Data Include data & evidence for each student outcome individually (e.g use a separate folder for each student outcome) 📂 Student Outcome Attainment Data 📂 Student Outcome 📄 Assessment Plan 📂 PI 1.1 📂 Assessment Instruments (e.g Problem & Rubric) 📂 Samples of Assessed Student Work 📂 PI 1.1 Data Set 📄 PI 1.1 Attainment Report 📂 PI 1.2 📂 PI 1.3 📄 SO1 Attainment Report 📂 Student Outcome 📂 Student Outcome 📂 Student Outcome 📂 Student Outcome Documentation of the Assessment & Evaluation Process Other Input for Continuous Improvement If other input is also used for continuous improvement of the program, include them in this folder 📂 Other Input for Continuous Improvement 📄 Industry Survey Report 📄 Alumni Survey Report 📄 IAB Meeting Minutes 📄 Faculty Council Meeting Minutes Documentation of the Assessment & Evaluation Process Evaluation & Improvement Actions Include documents/materials that show: ▪ Summaries of data collected and aggregated evaluation results for the cycle, illustrating current attainment of each SO and trends in attainment over time (tabular or graphical presentation is recommended.) ▪ Documentation of how the results of assessment and evaluation of the attainment of SOs are systematically used as input for the program’s continuous improvement actions ▪ Evidence of deliberations, decisions, and actions which have been implemented because of the evaluation of student attainment of the SOs Evidence might include evaluation reports, agendas, faculty meeting minutes, or memos USE OF DASHBOARD – not required but will impress evaluators/assessors 67% Student Outcome An ability to apply knowledge, techniques, skills and modern tools of mathematics, science, engineering, and technology to solve broadly-defined engineering problems appropriate to the discipline 100 90 80 70 60 50 40 30 20 10 PI 1.1 PI 1.2 PI 1.3 Make sure to demonstrate that your aggregation method is NOT average of averages USE OF DASHBOARD – not required but will impress evaluators/assessors 67% 75% 64% 84% 79% Student Outcome Student Outcome Student Outcome Student Outcome Student Outcome An ability to apply knowledge, techniques, skills and modern tools of mathematics, science, engineering, and technology to solve broadly-defined engineering problems appropriate to the discipline An ability to design systems, components, or processes meeting specified needs for broadly-defined engineering problems appropriate to the discipline An ability to apply written, oral, and graphical communication in broadlydefined technical and nontechnical environments; and an ability to identify and use appropriate technical literature An ability to conduct standard tests, measurements, and experiments and to analyze and interpret the results to improve processes An ability to function effectively as a member as well as a leader on technical teams 100 100 100 100 100 90 90 90 90 90 80 80 80 80 80 70 70 70 70 70 60 60 60 60 60 50 50 50 50 50 40 40 40 40 40 30 30 30 30 30 20 20 20 20 20 10 10 10 10 10 0 PI 1.1 PI 1.2 PI 1.3 PI 2.1 PI 2.2 PI 2.3 PI3.1 PI3.2 PI3.3 PI3.4 PI4.1 PI4.2 PI4.3 PI5.1 PI5.2 PI5.3  Assessment is not a controlled experiment  This is a data-informed, not data-driven process Evaluation  Take advantage of faculty wisdom and insight ▪ Not just anecdotal, but includes human element as well ▪ Data tell you WHAT ▪ Wisdom tells you WHY  Improvements should be linked to principles of student learning – focus mainly on student learning  Evaluation = data + wisdom ▪ Data are necessary but not sufficient Quiz: Assessment & Evaluation of Student Outcome Attainment Data/Evidence Interpretation Data Collection Improvement Decisions and Actions Developing PIs for each SO Collecting and preparing data Linking PIs to courses Using relevant & appropriate measures Creating assessment plan worksheet (maybe) using appropriate sampling methods ASSESSMENT PLANNING DATA COLLECTION ASSESSMENT Assessment Evaluation Assessment Planning Interpreting the data and evidence accumulated through assessment processes Determining the extent to which student outcomes are being attained DATA/EVIDENCE INTERPRETATION Making decisions and implement corrective actions regarding program improvement IMPROVEMENT DECISIONS AND ACTIONS EVALUATION FACULTY INVOLVEMENT  Average of averages of grades are not appropriate assessment data  Not all assessment data are equal – our emphasis is on direct evidence related to specific PIs Key Takeaways  Assessment results may use percentages but the numbers of students involved in those calculations should be evident  Assessment data need to be directly connected to program SOs, not CLOs  An aggregation or “roll-up” of assessment data by PSO is the goal – so SO(s) with weakest attainment level can be identified and addressed  Use of PIs and development of related assessment data related to course work already being graded can reduce assessment workload for a program’s faculty Thank you very much for your participation! ... What about grading of student work? ▪ A laboratory report? ▪ A final project report? ▪ A student presentation? ▪ Student team work? Yes! But data have to be more than just the student grades! Remember
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