with PreNRT as covariate Teaching and Learning with Data Using Audience Response System (ARS) Technology Nina Trocky, DNP, RN, NE-BC Lily Fountain, MS, PhD(c), CNM, RN Lynn Chen, PhD Background Methods Student Outcomes Results The teaching decision tree with ARS was implemented with no decrease in test scores. There were no significant differences between control and intervention groups on the students’ learning outcomes scores, when controlling for the pretest scores. ARS (“clickers”) is an interactive learning technology employed in different disciplines and types of courses. In the health sciences, measured outcomes include student satisfaction and single test scores (Efstathiou, 2011; Lantz, 2010). Researchers conducted this pilot study to determine the feasibility of utilizing a decision tree with student response data from ARS in a nursing research class. Turning Technologies (2013) ARS software was used to display each question. This classroom technology offered instructors the opportunity to immediately obtain student responses to the questions and utilize the response data to modify their teaching strategies according to a teaching decision tree (see below) and to examine the effects on learning outcomes, interest and satisfaction. A convenience sample of all four sections of an entry level nursing research course at a large Mid-Atlantic university was used. Two sections were assigned as the control group (non-ARS group) (n=47) and the other two sections were assigned as the intervention group (ARS group) (n=31). A quasi-experimental nonequivalent control group pretest-posttest design was used. IRB approval was secured. The intervention group used the ARS technology with the teaching decision tree during classes, while the control group did not. Both groups used the same in-class PowerPoint presentation slides and multiple-choice practice questions (see example below). Based upon the percentage of students selecting the correct response to each question, intervention instructors implemented the teaching decision tree: reteach, refer the students to peer discussion, or continue on to the next topic using a modified decision tree (Lasry, 2008; Mazur, 1997). Student outcomes measured: 1) Learning outcomes: exam scores, research article critique score, and pre-post Nursing Research Test (NRT) scores; Student interest; and Student satisfaction.   Group ANCOVA with PreNRT as covariate Control (n=47) Intervention (n=31) Mean SD F- statistics P- value Effect Size (η2) Pretest Nursing Research Test 15.40 2.69 14.45 2.57 Posttest Nursing Research Test 19.00 3.62 17.71 4.58 0.39 0.536 0.005 All Exams Average Score 88.36 6.45 85.94 6.70 1.14 0.288 0.015 Pretest Interest 39.91 9.47 37.77 10.85 0.87 0.355 0.011 Posttest Interest 37.00 10.28 32.10 13.00 3.13 0.081 0.040 Satisfaction 3.33 0.97 3.01 1.15 1.60 0.21 0.021 Brief Lecture Practice Question: Students Vote <60% Answer Correctly 60-80% >80% RETEACH REFER to Peer Discussion CONTINUE After clarifying misperceptions Students Revote Conclusions and Recommendations This study adds to the research base on the evaluation of technology-facilitated teaching strategies by specifically documenting the feasibility of using an ARS teaching decision tree in an entry level nursing research course. Recommendations for future research: Consider instructors’ learning curve using the technology with the decision tree; Consider the impact of the number of questions, their content and placement on learning outcomes; Control for peer discussion in the control group sections; Measure peer discussion specifically; Evaluate ARS technology and peer discussions in student satisfaction evaluation items. Research Aims Results Acknowledgements Feasibility Results Our criterion of recruitment of 50% of eligible students was greatly exceeded for the recruitment rate, and our criterion of a 90% retention rate was not met but the retention rate was acceptably high. Aim 1- Determine the recruitment rates, retention rates, and potential instructor and data management problems. Aim 2- Determine the influence of a protocol directing teacher responses to ARS data, using a teaching decision tree, on student learning outcomes. Aim 3- Determine the effect of the use of ARS upon student satisfaction and interest in nursing research. We would like to acknowledge the University of Maryland School of Nursing Dean’s Teaching Scholar program which funded this research. We would also like to thank Dr. Louise Jenkins, Kathy Fornili, and colleagues who provided suggestions and support for this research. Eligible N Recruitment Retention 156 113 (72%) 78 (69%) Contact Information Nina Trocky trocky@son.umaryland.edu Lily Fountain fountain@son.umaryland.edu Lynn Chen chen@son.umaryland.edu