Wednesday, December 16, 2015

Planning Assessments

Introduction
For this assessment I will be focusing on my 10th grade MYP PreCalculus class who are working towards mastery of the Common Core State Standard: HSS-ID.C.7. Interpret the slope (rate of change) and the intercept (constant term) of a linear fit in the context of the data.  

This blog entry, for  the TEACH-NOW Module 5, Unit 2, Activity 2, is focused on an objective that was developed in Unit 1 - By the end of this unit, when given a set of raw data, 10th grade math students will be able to consistently represent the data as a scatter plot that is appropriately labeled and includes an appropriate scale.  (Based on the December 13 virtual class discussion, the objective was slightly modified to fit my school's context since we are an MYP school and do not use percentages).  

As a means to track student progress towards the reaching the standard, I have designed the following four formative assessments that lead to a larger, more comprehensive summative assessment:

Formative Assessment #1
The students will collect measurements of each others arm span and height.  It will be recorded and share in a single Google Spreadsheet.  The students will make a copy of the spreadsheet for their own analysis.  In their own copy of the Google Sheets the students will create a scatter plot. After successfully completing the task in Google Sheets, the students will repeat the task in MS Excel, Apple's Numbers, and their TI-nSpire graphing calculator.  For each program the students will receive verbal feedback from their peers and the teacher as to the appropriateness of the scatter plot.

Formative Assessment 2
Using the same data and scatter plot as in the first formative assessment task, the students will use the features in Google Sheets to properly label each of the axes, include a title on the graph, and a legend.   This will  be repeated in MS Excel, Apple's Numbers, and their TI-nSpire graphing calculator.  For each program the students will receive verbal feedback from their peers and the teacher as to the appropriateness of the labels, titles and legends.

Formative Assessment 3
Using the same data and scatter plot as in the second formative assessment task, the students will features in Google Sheets to create a line of best fit, linear regression equation and r-value (correlation coefficient) for the data.

Formative Assessment 4
Using the r-value from the third formative assessment task, the students will interpret the correlation of the data and how that will impact the appropriateness of the data to make predictions about the relationship between arm span and height.  This task will require no technology, however will be done in groups of three as a discussion.  Students and teachers will offer formative feedback to students in order to ensure that students are making sound, data-based predictions.

Rationale
In breaking down this larger task into smaller task, there is greater opportunity for the teacher to guide the students with formative feedback so that their end product is of high quality.  Since the summative task for this unit is for students to take a large set of raw data and carry our a regression analysis in order to make predictions and subsequent informed decisions on the loaning of money through KIVA, it is important that they are able to display the data appropriately and in a way that is not misleading.  One of the biggest areas of growth for many of the students I encounter in 10th grade is there inability to create appropriate graphs.  In having them do the regression in parts the teacher ensures that they have the right product before carrying out the next task.  In doing so, the overall product will not be impacted by a mistake in the formation stages of the product.

Since the real world uses multiple applications to do this type of work, and since our students have access to all kinds of spreadsheet programs, it is also important that they encounter a variety of applications in the formative stages of the unit.  For the summative, the students will be able to choose the application that they feel most comfortable with.  However, it is noted for the students that the TI-nSpire should be mastered as it is the only tool allowed for tests and IBDP examinations.

Finally, the fourth task is designed as a practice for the summative task, which will ask students to interpret the r-value for the KIVA data and if their predictions are sound or not.

No comments:

Post a Comment