Facilitator: Angela Kapp Authentic Assessment Session 2 Session 2 Level 2 Minnesota Department of Human Services

Introductions Welcome and Introductions Housekeeping Overview of Sessions

Training Objectives To review, understand, and build skills around the foundational ideas of authentic assessment, including the use of the Early Childhood Indicators of Progress To understand the history of authentic assessment and current trends within the early care and education field To gain knowledge and skills in including parents within the authentic assessment process, including sharing data with parents. To understand the purposes for and uses of authentic assessment data to inform practice To build skills around data collection, data analysis, and data reporting

Learning and Practicing the Authentic Assessment Cycle

Observation/Data Recording Why do we observe, collect work samples, and develop portfolios? What are the best practices in observation? What are some strategies you use to gather data/information? What strategies have you used that didn’t work for you?

Potential Tools Anecdotal Records Running Records/Narratives Time Sampling Frequency Counts Checklists Work Samples/Portfolios

Practice: Observation (Individual)

Joy on the Playground Using the forms provided, answer the following questions: What did you notice? What did you wonder? What skills did Joy exhibit? What developmental domains were represented in the video? What did you expect to see her do? Did you notice any potential concerns?

Practice: Observation (Group)

Draco and Friends at a Restaurant Using the forms provided, answer the following questions: What did you notice? What did you wonder? What skills were exhibited? What developmental domains were represented in the video? What did you expect to see her do? Did you notice any potential concerns?

What’s Next? What do you do with all these observations? The data you gather (observations, samples of work, video, etc.) should reveal what a child is doing well and where there may be concerns. All curriculum/instructional decisions must be made using data, rather than hunches. The quality of your observations directly impact the choices you make for an individual child or the group of children with whom you are working.

Types of Data Quantitative: any information that can be measured and uses numbers Frequencies Demographic data (age, gender, number of siblings, etc.) Scores on a screening tool Qualitative: any data that can be described, but not measured Anecdotes Written observations Parent report

Data Analysis Analysis of collected data may include: Scanning Looking for Patterns/Trends Frequencies Averages Organizing data by age, gender, etc.

Data Analysis Continued Aggregating Data: grouping data into larger chunks of information in order to look for group patterns Disaggregating Data: breaking data down into smaller chunks of information in order to look for patterns Data analysis does not have to involve complicated formulas/statistics!

Practice: Analysis of Collected Data In small groups, please review the data you have been provided and answer the questions related to those data. When you are finished, as a small group, choose one of the data sets and write one goal for that child or one goal for the group of children.

ACTIVITY: Analysis of Collected Data What was your goal? What made you decide on that goal? What data were the most helpful to you in making a decision about a goal? How did you use the ECIPs during your analysis? What additional information would you want?

Using Data to Inform Program Program Evaluation and Strategic Planning: Authentic assessment data can also be used to determine if your program/curriculum is being implemented appropriately. You may choose to review authentic assessment data to help you determine new goals for your early care environment.

Next Step... Once you’ve analyzed the data and identified a goal for a child or a group of children, how do you use that information to help children develop and grow? Based on your knowledge and experience, you now interpret the data and develop hypotheses.

Data Interpretation Data Interpretation: The process of making sense of data that has been collected and analyzed The process of assigning meaning to the collected information and determining the conclusions, significance, and implications of the findings.

Developing Hypotheses Hypothesis: your “best guess” at why the behavior is occurring. Based on the data, the early childhood indicators of progress, family report, the curriculum you’re using, and your own experience with and knowledge of the child’s behavior and skills, you can develop a hypothesis about how to best support the child.

Practice Developing Hypotheses Develop at least 2 hypotheses for the data you have.

Closing

One completely new idea One useful idea One idea you will share with parent/friend/colleague Homework: Examples of using data Evaluation

Thank you for attending!