«COGNITIVE TRAINER CHARACTERISTICS THAT PREDICT OUTCOMES FOR STUDENTS WITH AND WITHOUT ADHD by Amy Lawson Moore DEBORA ADLER, EdD, Faculty Mentor and ...»
COGNITIVE TRAINER CHARACTERISTICS THAT PREDICT OUTCOMES
FOR STUDENTS WITH AND WITHOUT ADHD
Amy Lawson Moore
DEBORA ADLER, EdD, Faculty Mentor and Chair
JOHN MOORE, PhD, Committee Member
ELENI PINNOW, PhD, Committee Member
Curtis Brant, PhD, Dean
Harold Abel School of Social and Behavioral Sciences
A Dissertation Presented in Partial Fulfillment
Of the Requirements for the Degree
Doctor of Philosophy Capella University March 2015 UMI Number: 3687613 All rights reserved
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789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, MI 48106 - 1346 © Amy Lawson Moore, 2015 Abstract The current study utilized a quantitative, non-experimental design with multiple regression analysis of survey and archived data to examine the predictive value of cognitive trainer characteristics (degree field, degree level, cognitive trainer certification level, pre-hire cognitive test score, and personality traits) on student outcome measures of general intelligence, working memory, long-term memory, and processing speed. The study sample included 150 cognitive trainers and the archived records of 1,195 students.
There were no statistically significant predictors of outcomes for students with ADHD.
For students without ADHD, a trainer degree in education predicted higher long-term memory scores (p =.002, sr2 =.017); a degree higher than a master’s predicted lower long-term memory scores (p =.004, sr2 =.015); a master trainer certification predicted higher long-term memory scores (p =.002, sr2 =.017), and extroverted trainer personality predicted higher processing speed scores (p =.005, sr2 =.01). Administrators of cognitive training programs may want to track trends in outcomes of students with and without ADHD who are trained by trainers with master certification, a degree in education, a post-master’s level degree, or extroverted personality. Limitations of the
Dedicated first to God who makes all things possible. To my husband, Jeff, for your unwavering love and tireless support over these four long years, for being as excited about my research as I am, for being the super-human fighter pilot brain and inspiration behind my love of cognitive psychology, and for never doubting my ability to do this.
You have all my love, all my life, with all my heart. To my sons Cael, Lawson, and Evan for cheering me on, for eating way too many pizzas so I could study late, for understanding when I couldn’t join you on an adventure because I was studying, for rescuing me from technological disasters, and for reminding me that someday you would call me “Dr. Mom”! I hope all three of you do this someday. I love you. To my parents who modeled a lifelong love of teaching and learning; to my mom (Katie) for being my first (and best) professional mentor and for always reminding me that “You can do it, Louie!”; to my dad (Bill) for loving me no matter what; to my dad (Jim) whose spirit of accomplishment will never stop inspiring me…I wish he could have lived long enough to see me do this; to my mom (Maureen) for setting the bar higher than anyone else…I just had to catch up; to my incredible in-laws Linda and Rick for saving a rapidly sinking ship so I could finish. I love you all.
This project was a team effort! I owe my first and greatest thanks to my mentor, Dr. Debora Adler, for rescuing me from a nearly-aborted take-off; for never expressing concern that my own ADHD would hamper my progress; for enforcing the limits that I continued to push; for publically celebrating every small victory for all of us; and for generously sharing your knowledge so that I could succeed. You rock!
I want to thank my committee members, Dr. John Moore and Dr. Eleni Pinnow, for your time, spot-on suggestions, and genuine interest in my work. I also owe thanks to Dr. Bill Huitt for telling me early on in this journey to buy myself a t-shirt saying, “You can watch me, you can join me, just don’t get in my way!” Finally, a great many thanks to Dr. Ken Gibson, Tanya Mitchell, Dean Tenpas, and Mark Finzel for inviting me into the field of cognitive training, and for supporting my efforts to accomplish this project.
Table 6. Correlations between Student Scores and Trainer Personality Traits 77 Table 7.
Collinearity Statistics for Education and Experience with IQ 78 Table 8. Collinearity Statistics for Education and Experience with IQ 78
Table 11. Collinearity Statistics for Education and Experience with Working Memory 84 Table 12.
Collinearity Statistics for Education and Experience with Working Memory 84
Table 19. Collinearity Statistics for Education and Experience with Processing Speed 97 Table 20.
Collinearity Statistics for Education and Experience with Processing Speed 97
Cognitive training is a broad term referring to interventions that enhance specific cognitive skills through repeated engagement in targeted mental tasks (Rabipour & Raz, 2012). Grounded in the assumption of neuroplasticity, cognitive training programs are designed to improve general intelligence as well as refine neural processes such as working memory, attention, and processing speed. Unlike tutoring and other academic interventions for acquiring content knowledge, cognitive training programs are designed to improve thinking and learning across domains through enhanced cognitive flexibility (Atkins, Bunting, Bolger, & Dougherty, 2011). With a clinical reach beyond computerdelivered “brain games”, cognitive trainers create individualized interventions for students that target specific cognitive deficits identified through pretesting with standardized assessments such as the Woodcock-Johnson III Tests of Cognitive Abilities (Woodcock, McGrew, & Mather, 2007) or the Gibson Test of Cognitive Skills (Gibson, 2000). Using a set of intensive game-like mental tasks, trainers deliver interventions oneon-one to students during one-hour sessions five days per week for a duration of 12 to 24 weeks (Gibson, 2007). The current study examined how cognitive trainer characteristics (personality traits, college major, degree level, certification level, pre-hire cognitive test score) predicted outcomes on measures of working memory, long-term memory, processing speed, and general intelligence for students with and without ADHD. Prior research suggested that such characteristics are all associated with instructor quality, student achievement, student persistence in intervention programs; and instructor use of ADHD intervention strategies (Bowers, 2006; Carlson, Lee, & Schroll, 2004; Charlebois, Vitaro, Normandeau, Brendgen, & Rondeau, 2004; Croninger, Rice, Rathbun, & Nishio, 2007; Fenderson, 2011; Garcia, 2010; Kneipp, Kelly, Biscoe, & Richard, 2010; Small, 2006). However, it is not clear how instructor traits predict cognitive training outcomes.
Furthermore, over 33% of students enrolled in a certain proprietary network of cognitive training programs in 2011 had been previously diagnosed with ADHD; and 67% of students reported problems with attention prior to enrollment (Gibson, 2011). Therefore, it was valuable to examine the association of cognitive trainer traits with learning outcomes of students with and without ADHD.
The current study was situated within in the field of educational psychology as cognitive and social cognitive lenses have framed over 98% of educational psychology research conducted since 1995 (Mitchell & McConnell, 2012). Not only do educational psychology researchers examine individual cognitive processes such as attention (Swanson, 2011) and memory (Swanson, 2008), they also study how innate skills and learning experiences influence cognitive performance (Hergenhahn & Henley, 2014).
Additionally, students with ADHD exhibit individual learning differences due to deficits in attention, working memory, and executive control (Brown, 2006), so a focus on outcomes for students with ADHD provided insight on the trainer characteristics needed for creating the positive learning conditions that contribute to their learning gains. With 11% of children in the United States diagnosed with ADHD (Visser et al., 2013), it was critical to identify factors that promote and enhance their academic success. Therefore, an examination of the trainer characteristics that predict cognitive training outcomes for students with and without ADHD was aligned with current research trends, and was an appropriate task for a researcher in the field of educational psychology.
Extant research has demonstrated support for the efficacy of cognitive training programs in both computer-based and face-to-face environments (Gibson, 2009; Holmes et al., 2009; Klingberg et al., 2005; Melby-Lervag & Hulme, 2013; Sonuga-Barke et al., 2013; Wegrzyn, Hearrington, Martin, & Randolph, 2012). However, prior studies focused on factors related to intervention tasks that predicted cognitive training gains rather than the characteristics of cognitive trainers that may predict training outcomes. It was unknown how the characteristics of cognitive trainers might predict training outcomes for students with or without ADHD. Through the lens of social cognitive theory, the current research examined the predictive variables of cognitive trainer characteristics on training outcomes for students with and without ADHD. Specifically, the study examined if the cognitive trainer characteristics of personality traits, college major, degree level, certification level, and pre-hire cognitive test score predicted learning outcomes in general intelligence, working memory, long-term memory, and processing speed as measured by the Woodcock Johnson III-Tests of Cognitive Abilities for students with and without ADHD.
The purpose of the current study was to investigate the characteristics of cognitive trainers that predicted cognitive training outcomes for students with and without ADHD.
Although prior research had demonstrated support for the efficacy of cognitive training programs (Gibson, 2009; Holmes et al., 2009; Klingberg et al., 2005; Melby-Lervag & Hulme, 2013; Sonuga-Barke et al., 2013; Wegrzyn, Hearrington, Martin, & Randolph, 2012), the factors unrelated to treatment tasks that predict cognitive training gains have not been identified. Further, it remains unclear how the characteristics of cognitive trainers might predict training outcomes. Knowledge of the predictive value of these trainer characteristics (including college degree and level, cognitive training certification level, personality traits, and pre-hire cognitive test scores) may assist program administrators in maximizing the benefits of the training for children and adolescents with ADHD through targeted trainer recruitment and appropriate matching of trainer and student. Because over 33% of students enrolled in a certain proprietary network of cognitive training programs in 2011 had been previously diagnosed with ADHD; and 67% of students reported problems with attention prior to enrollment (Gibson, 2011), it was important to examine the association of cognitive trainer traits with learning outcomes of students with and without ADHD.
Dominated by efficacy studies, past research on cognitive training revealed improvements in attention (Gibson, 2009; Rabiner, Murray, Skinner, & Malone, 2010), memory (Beck, Hanson, & Puffenberger, 2010; Carpenter, 2009; Gibson et al., 2011), and reading comprehension (Shalev, Tsal, & Mevorach, 2007), as well as a reduction in hyperactivity (Vander der Oord et al., 2012). Prior studies showed improvements in attention, processing speed, working memory, long-term memory, phonemic awareness, auditory and visual processing, logic and reasoning, sensory motor skills, oppositional behavior, general intelligence, and school performance (Carpenter, 2009; Jedlicka, 2012;
Luckey, 2006; Luckey, 2009; Pfister, 2013). Prior research had also indicated a relationship between instructor characteristics and student achievement in a variety of settings including schools (Carlson, Lee, & Schroll-Westat, 2004; Edmonds, 2010;
Garcia, Kupczynski, & Holland, 2011; Kneipp, Kelly, Biscoe, & Richard, 2010), tutoring (Putra, 2013), corporate training (Ghosh, Satyawadi, Joshi, Ranjan, & Singh, 2012), and mental health (Charlebois, Vitaro, Normandeau, Brendgen, & Rondeau, 2004; Siqueland et al., 2000). The current study added to the scientific knowledge base on cognitive training by filling a gap in the literature with an examination of trainer characteristics that predict outcomes for students with and without ADHD; and also added to the knowledge base on the relationship between instructor characteristics and student outcomes by examining that relationship in the cognitive training setting. Given the theoretical support for relationships as moderators to learning and the development of self-efficacy for learning (Bandura, 1997; Schunk & Miller, 2002), this relationship should indeed have been examined in the context of cognitive training.
Educational psychology researchers examine individual cognitive processes such as attention (Swanson, 2011) and memory (Swanson, 2008), as well as how innate skills and learning experiences influence cognitive performance (Hergenhahn & Henley, 2014).