Teacher Text is a student learning and student engagement practice that has statistically increased exam, quiz, paper, and satisfaction scores in online and blended learning courses. Utilizing texting, students are informed of course events, engaged in course content, current events, and participate in adaptive response learning. Experimental groups have statistically (p<.05) demonstrated significance versus control groups in repeated studies demonstrating replicability, scalability, and consistency.
Teacher text started in a classroom experiment of a blended undergraduate psychology class of 31 students. A control group consisted of 15 students and the experimental group consisted of 16 students. Participants self-selected in the experiment through syllabus invitation and the first 16 to volunteer were accepted. They were randomly assigned a designation of student 1, student 2... student 16 by a research assistant. There were four interactions per week. 1.) an informative text reminding them of upcoming learning experiences, 2.) a text connecting course material to a current event, 3.) an encouraging message based on class observation/progress, and 4.) an option for them to text the teacher a question, comment, concern, or open-ended subject matter. For the initial experiment, a text-based review for the final exam was used.
To mitigate subject bias, participation was changed to random selection to populate control and experimental groups.
Teacher Text was applied to blended and online courses to compare applicability for blended and online learning environments and replicability of the teacher text condition.
Various texting apps have been used to and we refrain from identifying a preferred app, but in an upcoming paper we are including examples of what we believe currently provide the best functionality for implementing Teacher Text.
Use of an adaptive application has been introduced to control for retrieval practice and learner self-regulation. This has been applied to all assessments. In the initial research, this was only applied to the final exam.
The adaptive portion of Teacher Text now has the ability to integrate with most LMS the application increasing scalability and usefulness for small and large classes.
Teacher Text has been implemented at Cisco College, Abilene Christian University, and Hardin-Simmons University demonstrating statistical significance in each application of the experimental conditions. The developmental psychology class are Cisco College, exam scores, quiz scores, written assignments, and course satisfaction scores were significantly higher in the experimental versus the control condition. There was no difference in the final exam score since the control students requested inclusion in Teacher Text to prepare for the final exam. At Abilene Christian University, it has been replicated in three fully online courses in the Masters of Education graduate program and is being used in two large lecture blended format classes (114 & 119) in Fall 2014. Results in two of the online courses demonstrated statistical significance in written papers, quizzes, and course satisfaction. However, no exams are given in the graduate program so no data was available. In the third course, the class size was below 12 so we did not use a control conditional but had higher course satisfaction scores than two previously taught course, but not at a level of statistical significance. At Hardin-Simmons University, Teacher Text was used in a blended format graduate and undergraduate level kinesiology course. Statistically significant results were demonstrated in exams and quizzes, but no written work was submitted. Course satisfaction scores were higher but not at a statistically significant level.
Teacher Text was used in another university and we are waiting upon data.
Teacher Text has demonstrated statistical significance in learning effectiveness in blended and online learning environments. The practice was developed for widespread adoption using existing technologies that students and faculty already possessed and would not require infrastructure modifications, data plans, or device purchase. All students can participate with a cell phone that possesses texting capabilities and ADA compliance can be accomplished with voice recognition capabilities on an IOS or Android device. Faculty satisfaction has been positive because it allows them to be more successful, allows their students to be more successful, and have increased course satisfaction scores from students. Faculty aren't required to text using a mobile device; rather, they can participate using a desktop or laptop to complete texts. Student satisfaction has increased allowing and encouraging students to use their devices to participate in academic activity and ways that are already an ambient part of the digital habits.
Rationale: The reason I developed Teacher Text was for scalability and economic inclusion. Current data suggests 99.9% of college-aged students have a cell phone with texting capabilities. This allows public, private, l, junior colleges, community colleges and other institutions to utilize texting without increasing student costs for purchasing technology or data plans. Minimalist equipment is needed due to operating outside the network and outside of class.This is a mobile learning starting point that engages and includes students, faculty, and institutions in an economical and inclusive learning practice. It provides a reliable and replicable starting point to increase learning outcomes and student engagement at minimal cost and infrastructure.
Teacher Text can fully implemented at no cost to students and minimal or no cost to an institution. One of the main advantages of Teacher Text is that it utilizes existing technology and leverages it to increase learning and engagement. ADA compliance and service to all students may necessitate use of an IOS or Android device with voice recognition.
Current Teacher Text data is being put into a paper to be presented at the OLC Orlando Conference and will be submitted for publication at the end of Fall 2014 semester when all current data has been tabulated. We have statistical results from six courses and waiting on data from a recent study and two experiments in Fall 2014. Have given several presentations on early data.