Team Shake App

You will be able to easily choose teams for games and sports based on students' skill or gender.

https://apps.apple.com/us/app/team-shake/id390812953

Assessment in physical education is a key accountability measure for both the student and the teacher.  The primary goal of assessment should be the enhancement of learning (NASPE, 2004), not an add-on (Nye, Dubay, Gilbert, & Wajciechowski, 2009).

Common reasons physical educators do not assess include a) “It takes up too much time.”  Teachers may feel they do not have enough time to spend collecting assessment data, when they only see the students for 40 minutes, once a week. b) “I don’t know how.”  Teachers might not know how to assess and/or what to assess. c) “It won’t change anything, why even bother.”  Teachers might assess and collect data, but do not use it to inform instruction.

Kahoot

Kahoot is an online platform, in which physical educators can create assessments such as quizzes, polls, and discussions. In addition, Kahoot is interactive and provides an engaging game-based educational platform for students (Kahoot!, 2014). Game-based learning has been used as a best practice approach to engaging students in reviewing class content in various classroom settings (Icard, 2014). 

One example of how Kahoot could be used in the physical education setting is to split the class into six groups to share a tablet for a quiz. Each group would be given one tablet, allowing students to work together to answer the quiz questions. First, students will follow simple on-screen instructions to ‘join’ the game. Next, the physical education teacher would project the quiz on a screen, and groups would begin participating in a Kahoot quiz. Kahoot provides real-time feedback, which is a great way to gauge student learning. The physical educator can review quiz content after each question, or at the conclusion of the quiz. If there was a question or multiple questions that a large percentage of the class marked incorrectly, the teacher might consider reviewing each question before moving on.

MetricMe: A Daily Health, Workout, Fitness & Exercise Tracker

MetricMe is perfect for physical educators because it was designed for individuals who already know why health and fitness metrics are important but want a simple way to track their progress (MetricMe, 2012). Physical education teachers may struggle to find the time during class to input and interpret student data. The MetricMe app keeps data organized and offers a host of analytics, graphs, and goal setting features to help gauge student success. The app is available on the App Store for iOS devises, such as an iPod, iPhone, iPad. Once the app is downloaded, it can be used without an internet connection and allows users to connect to a Dropbox account. Thus, allowing MetricMe to automatically backup classroom data. Users can export records into a readable, spreadsheet document (CSV).  

The MetricMe app could be particularly useful for physical education teachers who teach fitness related or weight training classes. This would allow the physical education teacher to have more time providing essential feedback to the learners, rather than spending instructional time collecting student data. Metrics can be created based on the following categories with MetricMe (Table 1).

SPSS repeated measures ANOVA tests if the means of 3 or more metric variables are all equal in some population. 
The simplest repeated measures ANOVA involves 3 outcome variables, all measured on 1 group of cases (often people). Whatever distinguishes these variables (sometimes just the time of measurement) is the within-subjects factor.

SPSS

Analyze - General Linear Model - Repeated Measuers

1. We may freely choose a name for our within-subjects factor. 

2. We may also choose a name for our measure: whatever each of the four variables is supposed to reflect. 

3. We now select all four variables and move them to the Within-subjects variables box with the arrow to the right.

4. Under Options we'll select Descriptive statistics.

5. Clicking Paste results in the syntax below.

Repeated Measures ANOVA Output - Mauchly’s Test

We now turn to Mauchly's test for the sphericity assumption. As a rule of thumb, sphericity is assumed if Sig. > 0.05. 

Repeated Measures ANOVA Output - Within-Subjects Effects

Since our data seem spherical, we'll ignore the Greenhouse-Geisser, Huynh-Feldt and lower bound results in the table below. We'll simply interpret the uncorrected results denoted as “Sphericity Assumed”.

Reporting the Measures ANOVA Result

When reporting a basic repeated-measures ANOVA, we usually report

• the descriptive statistics table
• the outcome of Mauchly's test and
• the outcome of the within-subjects tests.

Repeated Measures ANOVA

Repeated measures ANOVA is

1. the extension of the dependent t-test

2. the equivalent of the one-way ANOVA, but for related, not independent groups. 

3. a within-subjects ANOVA or

4. a ANOVA for correlated samples.

5. a test to detect any overall differences between related means.

The dependent variable needs to be continuous (interval or ratio) and the independent variable categorical (either nominal or ordinal).

When to use a Repeated Measures ANOVA (Two Types)

We can analyze data using a repeated measures ANOVA for two types of study design.

Studies that investigate either

(1) changes in mean scores over three or more time points

(2) differences in mean scores under three or more different conditions.

The important point with these two study designs is that the same people are being measured more than once on the same dependent variable (i.e., why it is called repeated measures).

In repeated measures ANOVA, the independent variable has categories called levels or related groups.

Where measurements are repeated over time, such as when measuring changes in skill levels due to an exercise-training programme, the independent variable is time. Each level (or related group) is a specific time point. Hence, for the exercise-training study, there would be three time points and each time-point is a level of the independent variable (a schematic of a time-course repeated measures design is shown below)