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- All Subjects: Educational technology
- All Subjects: Academic Achievement
- All Subjects: College Enrollment
- Creators: Atkinson, Robert K
- Resource Type: Text
- Status: Published
Description
This study empirically evaluated the effectiveness of the instructional design, learning tools, and role of the teacher in three versions of a semester-long, high-school remedial Algebra I course to determine what impact self-regulated learning skills and learning pattern training have on students' self-regulation, math achievement, and motivation. The 1st version was a business-as-usual traditional classroom teaching mathematics with direct instruction. The 2rd version of the course provided students with self-paced, individualized Algebra instruction with a web-based, intelligent tutor. The 3rd version of the course coupled self-paced, individualized instruction on the web-based, intelligent Algebra tutor coupled with a series of e-learning modules on self-regulated learning knowledge and skills that were distributed throughout the semester. A quasi-experimental, mixed methods evaluation design was used by assigning pre-registered, high-school remedial Algebra I class periods made up of an approximately equal number of students to one of the three study conditions or course versions: (a) the control course design, (b) web-based, intelligent tutor only course design, and (c) web-based, intelligent tutor + SRL e-learning modules course design. While no statistically significant differences on SRL skills, math achievement or motivation were found between the three conditions, effect-size estimates provide suggestive evidence that using the SRL e-learning modules based on ARCS motivation model (Keller, 2010) and Let Me Learn learning pattern instruction (Dawkins, Kottkamp, & Johnston, 2010) may help students regulate their learning and improve their study skills while using a web-based, intelligent Algebra tutor as evidenced by positive impacts on math achievement, motivation, and self-regulated learning skills. The study also explored predictive analyses using multiple regression and found that predictive models based on independent variables aligned to student demographics, learning mastery skills, and ARCS motivational factors are helpful in defining how to further refine course design and design learning evaluations that measure achievement, motivation, and self-regulated learning in web-based learning environments, including intelligent tutoring systems.
ContributorsBarrus, Angela (Author) / Atkinson, Robert K (Thesis advisor) / Van de Sande, Carla (Committee member) / Savenye, Wilhelmina (Committee member) / Arizona State University (Publisher)
Created2013
Description
Statistics is taught at every level of education, yet teachers often have to assume their students have no knowledge of statistics and start from scratch each time they set out to teach statistics. The motivation for this experimental study comes from interest in exploring educational applications of augmented reality (AR) delivered via mobile technology that could potentially provide rich, contextualized learning for understanding concepts related to statistics education. This study examined the effects of AR experiences for learning basic statistical concepts. Using a 3 x 2 research design, this study compared learning gains of 252 undergraduate and graduate students from a pre- and posttest given before and after interacting with one of three types of augmented reality experiences, a high AR experience (interacting with three dimensional images coupled with movement through a physical space), a low AR experience (interacting with three dimensional images without movement), or no AR experience (two dimensional images without movement). Two levels of collaboration (pairs and no pairs) were also included. Additionally, student perceptions toward collaboration opportunities and engagement were compared across the six treatment conditions. Other demographic information collected included the students' previous statistics experience, as well as their comfort level in using mobile devices. The moderating variables included prior knowledge (high, average, and low) as measured by the student's pretest score. Taking into account prior knowledge, students with low prior knowledge assigned to either high or low AR experience had statistically significant higher learning gains than those assigned to a no AR experience. On the other hand, the results showed no statistical significance between students assigned to work individually versus in pairs. Students assigned to both high and low AR experience perceived a statistically significant higher level of engagement than their no AR counterparts. Students with low prior knowledge benefited the most from the high AR condition in learning gains. Overall, the AR application did well for providing a hands-on experience working with statistical data. Further research on AR and its relationship to spatial cognition, situated learning, high order skill development, performance support, and other classroom applications for learning is still needed.
ContributorsConley, Quincy (Author) / Atkinson, Robert K (Thesis advisor) / Nguyen, Frank (Committee member) / Nelson, Brian C (Committee member) / Arizona State University (Publisher)
Created2013
Description
Researchers have postulated that math academic achievement increases student success in college (Lee, 2012; Silverman & Seidman, 2011; Vigdor, 2013), yet 80% of universities and 98% of community colleges require many of their first-year students to be placed in remedial courses (Bettinger & Long, 2009). Many high school graduates are entering college ill prepared for the rigors of higher education, lacking understanding of basic and important principles (ACT, 2012). The desire to increase academic achievement is a wide held aspiration in education and the idea of adapting instruction to individuals is one approach to accomplish this goal (Lalley & Gentile, 2009a). Frequently, adaptive learning environments rely on a mastery learning approach, it is thought that when students are afforded the opportunity to master the material, deeper and more meaningful learning is likely to occur. Researchers generally agree that the learning environment, the teaching approach, and the students' attributes are all important to understanding the conditions that promote academic achievement (Bandura, 1977; Bloom, 1968; Guskey, 2010; Cassen, Feinstein & Graham, 2008; Changeiywo, Wambugu & Wachanga, 2011; Lee, 2012; Schunk, 1991; Van Dinther, Dochy & Segers, 2011). The present study investigated the role of college students' affective attributes and skills, such as academic competence and academic resilience, in an adaptive mastery-based learning environment on their academic performance, while enrolled in a remedial mathematics course. The results showed that the combined influence of students' affective attributes and academic resilience had a statistically significant effect on students' academic performance. Further, the mastery-based learning environment also had a significant effect on their academic competence and academic performance.
ContributorsFoshee, Cecile Mary (Author) / Atkinson, Robert K (Thesis advisor) / Elliott, Stephen N. (Committee member) / Horan, John (Committee member) / Arizona State University (Publisher)
Created2013
Description
This study explored three methods to measure cognitive load in a learning environment using four logic puzzles that systematically varied in level of intrinsic cognitive load. Participants' perceived intrinsic load was simultaneously measured with a self-report measure--a traditional subjective measure--and two objective, physiological measures based on eye-tracking and EEG technology. In addition to gathering self-report, eye-tracking data, and EEG data, this study also captured data on individual difference variables and puzzle performance. Specifically, this study addressed the following research questions: 1. Are self-report ratings of cognitive load sensitive to tasks that increase in level of intrinsic load? 2. Are physiological measures sensitive to tasks that increase in level of intrinsic load? 3. To what extent do objective physiological measures and individual difference variables predict self-report ratings of intrinsic cognitive load? 4. Do the number of errors and the amount of time spent on each puzzle increase as the puzzle difficulty increases? Participants were 56 undergraduate students. Results from analyses with inferential statistics and data-mining techniques indicated features from the physiological data were sensitive to the puzzle tasks that varied in level of intrinsic load. The self-report measures performed similarly when the difference in intrinsic load of the puzzles was the most varied. Implications for these results and future directions for this line of research are discussed.
ContributorsJoseph, Stacey (Author) / Atkinson, Robert K (Thesis advisor) / Johnson-Glenberg, Mina (Committee member) / Nelson, Brian (Committee member) / Klein, James (Committee member) / Arizona State University (Publisher)
Created2013
Description
Writing instruction poses both cognitive and affective challenges, particularly for adolescents. American teens not only fall short of national writing standards, but also tend to lack motivation for school writing, claiming it is too challenging and that they have nothing interesting to write about. Yet, teens enthusiastically immerse themselves in informal writing via text messaging, email, and social media, regularly sharing their thoughts and experiences with a real audience. While these activities are, in fact, writing, research indicates that teens instead view them as simply "communication" or "being social." Accordingly, the aim of this work was to infuse formal classroom writing with naturally engaging elements of informal social media writing to positively impact writing quality and the motivation to write, resulting in the development and implementation of Sparkfolio, an online prewriting tool that: a) addresses affective challenges by allowing students to choose personally relevant topics using their own social media data; and b) provides cognitive support with a planner that helps develop and organize ideas in preparation for writing a first draft. This tool was evaluated in a study involving 46 eleventh-grade English students writing three personal narratives each, and including three experimental conditions: a) using self-authored social media post data while planning with Sparkfolio; b) using only data from posts authored by one's friends while planning with Sparkfolio; and c) a control group that did not use Sparkfolio. The dependent variables were the change in writing motivation and the change in writing quality that occurred before and after the intervention. A scaled pre/posttest measured writing motivation, and the first and third narratives were used as writing quality pre/posttests. A usability scale, logged Sparkfolio data, and qualitative measures were also analyzed. Results indicated that participants who used Sparkfolio had statistically significantly higher gains in writing quality than the control group, validating Sparkfolio as effective. Additionally, while nonsignificant, results suggested that planning with self-authored data provided more writing quality and motivational benefits than data authored by others. This work provides initial empirical evidence that leveraging students' own social media data (securely) holds potential in fostering meaningful personalized learning.
ContributorsSadauskas, John (Author) / Atkinson, Robert K (Thesis advisor) / Savenye, Wilhelmina (Committee member) / Liu, Huan (Committee member) / Arizona State University (Publisher)
Created2014
Description
A recorded tutorial dialogue can produce positive learning gains, when observed and used to promote discussion between a pair of learners; however, this same effect does not typically occur when an leaner observes a tutorial dialogue by himself or herself. One potential approach to enhancing learning in the latter situation is by incorporating self-explanation prompts, a proven technique for encouraging students to engage in active learning and attend to the material in a meaningful way. This study examined whether learning from observing recorded tutorial dialogues could be made more effective by adding self-explanation prompts in computer-based learning environment. The research questions in this two-experiment study were (a) Do self-explanation prompts help support student learning while watching a recorded dialogue? and (b) Does collaboratively observing (in dyads) a tutorial dialogue with self-explanation prompts help support student learning while watching a recorded dialogue? In Experiment 1, 66 participants were randomly assigned as individuals to a physics lesson (a) with self-explanation prompts (Condition 1) or (b) without self-explanation prompts (Condition 2). In Experiment 2, 20 participants were randomly assigned in 10 pairs to the same physics lesson (a) with self-explanation prompts (Condition 1) or (b) without self-explanation prompts (Condition 2). Pretests and posttests were administered, as well as other surveys that measured motivation and system usability. Although supplemental analyses showed some significant differences among individual scale items or factors, neither primary results for Experiment 1 or Experiment 2 were significant for changes in posttest scores from pretest scores for learning, motivation, or system usability assessments.
ContributorsWright, Kyle Matthew (Author) / Atkinson, Robert K (Thesis advisor) / Savenye, Wilhelmina (Committee member) / Nelson, Brian (Committee member) / Arizona State University (Publisher)
Created2018
Description
The present study explored the use of augmented reality (AR) technology to support cognitive modeling in an art-based learning environment. The AR application used in this study made visible the thought processes and observational techniques of art experts for the learning benefit of novices through digital annotations, overlays, and side-by-side comparisons that when viewed on mobile device appear directly on works of art.
Using a 2 x 3 factorial design, this study compared learner outcomes and motivation across technologies (audio-only, video, AR) and groupings (individuals, dyads) with 182 undergraduate and graduate students who were self-identified art novices. Learner outcomes were measured by post-activity spoken responses to a painting reproduction with the pre-activity response as a moderating variable. Motivation was measured by the sum score of a reduced version of the Instructional Materials Motivational Survey (IMMS), accounting for attention, relevance, confidence, and satisfaction, with total time spent in learning activity as the moderating variable. Information on participant demographics, technology usage, and art experience was also collected.
Participants were randomly assigned to one of six conditions that differed by technology and grouping before completing a learning activity where they viewed four high-resolution, printed-to-scale painting reproductions in a gallery-like setting while listening to audio-recorded conversations of two experts discussing the actual paintings. All participants listened to expert conversations but the video and AR conditions received visual supports via mobile device.
Though no main effects were found for technology or groupings, findings did include statistically significant higher learner outcomes in the elements of design subscale (characteristics most represented by the visual supports of the AR application) than the audio-only conditions. When participants saw digital representations of line, shape, and color directly on the paintings, they were more likely to identify those same features in the post-activity painting. Seeing what the experts see, in a situated environment, resulted in evidence that participants began to view paintings in a manner similar to the experts. This is evidence of the value of the temporal and spatial contiguity afforded by AR in cognitive modeling learning environments.
Using a 2 x 3 factorial design, this study compared learner outcomes and motivation across technologies (audio-only, video, AR) and groupings (individuals, dyads) with 182 undergraduate and graduate students who were self-identified art novices. Learner outcomes were measured by post-activity spoken responses to a painting reproduction with the pre-activity response as a moderating variable. Motivation was measured by the sum score of a reduced version of the Instructional Materials Motivational Survey (IMMS), accounting for attention, relevance, confidence, and satisfaction, with total time spent in learning activity as the moderating variable. Information on participant demographics, technology usage, and art experience was also collected.
Participants were randomly assigned to one of six conditions that differed by technology and grouping before completing a learning activity where they viewed four high-resolution, printed-to-scale painting reproductions in a gallery-like setting while listening to audio-recorded conversations of two experts discussing the actual paintings. All participants listened to expert conversations but the video and AR conditions received visual supports via mobile device.
Though no main effects were found for technology or groupings, findings did include statistically significant higher learner outcomes in the elements of design subscale (characteristics most represented by the visual supports of the AR application) than the audio-only conditions. When participants saw digital representations of line, shape, and color directly on the paintings, they were more likely to identify those same features in the post-activity painting. Seeing what the experts see, in a situated environment, resulted in evidence that participants began to view paintings in a manner similar to the experts. This is evidence of the value of the temporal and spatial contiguity afforded by AR in cognitive modeling learning environments.
ContributorsShapera, Daniel Michael (Author) / Atkinson, Robert K (Thesis advisor) / Nelson, Brian C (Committee member) / Erickson, Mary (Committee member) / Arizona State University (Publisher)
Created2016
Description
Expectation for college attendance in the United States continues to rise as more jobs require degrees. This study aims to determine how parental expectations affect high school students in their decision to attend college. By examining parental expectations that were placed on current college students prior to and during the application period, we can determine the positive and negative outcomes of these expectations as well as the atmosphere they are creating. To test the hypothesis, an online survey was distributed to current ASU and Barrett, Honors College students regarding their experience with college applications and their parents' influence on their collegiate attendance. A qualitative analysis of the data was conducted in tandem with an analysis of several case studies to determine the results. These data show that parental expectations are having a significant impact on the enrollment of high school students in college programs. With parents placing these expectations on their children, collegiate enrollment will continue to increase. Further studies will be necessary to determine the specific influences these expectations are placing on students.
ContributorsScheller, Sara Matheson (Co-author) / Johnson, Benjamin (Co-author) / Kappes, Janelle (Thesis director) / Fairbanks, Elizabeth (Committee member) / Division of Teacher Preparation (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Expectation for college attendance in the United States continues to rise as more jobs require degrees. This study aims to determine how parental expectations affect high school students in their decision to attend college. By examining parental expectations that were placed on current college students prior to and during the application period, we can determine the positive and negative outcomes of these expectations as well as the atmosphere they are creating. To test the hypothesis, an online survey was distributed to current ASU and Barrett, Honors College students regarding their experience with college applications and their parents' influence on their collegiate attendance. A qualitative analysis of the data was conducted in tandem with an analysis of several case studies to determine the results. These data show that parental expectations are having a significant impact on the enrollment of high school students in college programs. With parents placing these expectations on their children, collegiate enrollment will continue to increase. Further studies will be necessary to determine the specific influences these expectations are placing on students.
ContributorsJohnson, Benjamin Howard (Co-author) / Scheller, Sara (Co-author) / Kappes, Janelle (Thesis director) / Fairbanks, Elizabeth (Committee member) / Department of Psychology (Contributor) / School of Social Transformation (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Evidence suggests that Augmented Reality (AR) may be a powerful tool for
alleviating certain, lightly held scientific misconceptions. However, many
misconceptions surrounding the theory of evolution are deeply held and resistant to
change. This study examines whether AR can serve as an effective tool for alleviating
these misconceptions by comparing the change in the number of misconceptions
expressed by users of a tablet-based version of a well-established classroom simulation to
the change in the number of misconceptions expressed by users of AR versions of the
simulation.
The use of realistic representations of objects is common for many AR
developers. However, this contradicts well-tested practices of multimedia design that
argue against the addition of unnecessary elements. This study also compared the use of
representational visualizations in AR, in this case, models of ladybug beetles, to symbolic
representations, in this case, colored circles.
To address both research questions, a one-factor, between-subjects experiment
was conducted with 189 participants randomly assigned to one of three conditions: non
AR, symbolic AR, and representational AR. Measures of change in the number and types
of misconceptions expressed, motivation, and time on task were examined using a pair of
planned orthogonal contrasts designed to test the study’s two research questions.
Participants in the AR-based condition showed a significantly smaller change in
the number of total misconceptions expressed after the treatment as well as in the number
of misconceptions related to intentionality; none of the other misconceptions examined
showed a significant difference. No significant differences were found in the total
number of misconceptions expressed between participants in the representative and
symbolic AR-based conditions, or on motivation. Contrary to the expectation that the
simulation would alleviate misconceptions, the average change in the number of
misconceptions expressed by participants increased. This is theorized to be due to the
juxtaposition of virtual and real-world entities resulting in a reduction in assumed
intentionality.
alleviating certain, lightly held scientific misconceptions. However, many
misconceptions surrounding the theory of evolution are deeply held and resistant to
change. This study examines whether AR can serve as an effective tool for alleviating
these misconceptions by comparing the change in the number of misconceptions
expressed by users of a tablet-based version of a well-established classroom simulation to
the change in the number of misconceptions expressed by users of AR versions of the
simulation.
The use of realistic representations of objects is common for many AR
developers. However, this contradicts well-tested practices of multimedia design that
argue against the addition of unnecessary elements. This study also compared the use of
representational visualizations in AR, in this case, models of ladybug beetles, to symbolic
representations, in this case, colored circles.
To address both research questions, a one-factor, between-subjects experiment
was conducted with 189 participants randomly assigned to one of three conditions: non
AR, symbolic AR, and representational AR. Measures of change in the number and types
of misconceptions expressed, motivation, and time on task were examined using a pair of
planned orthogonal contrasts designed to test the study’s two research questions.
Participants in the AR-based condition showed a significantly smaller change in
the number of total misconceptions expressed after the treatment as well as in the number
of misconceptions related to intentionality; none of the other misconceptions examined
showed a significant difference. No significant differences were found in the total
number of misconceptions expressed between participants in the representative and
symbolic AR-based conditions, or on motivation. Contrary to the expectation that the
simulation would alleviate misconceptions, the average change in the number of
misconceptions expressed by participants increased. This is theorized to be due to the
juxtaposition of virtual and real-world entities resulting in a reduction in assumed
intentionality.
ContributorsHenry, Matthew McClellan (Author) / Atkinson, Robert K (Thesis advisor) / Johnson-Glenberg, Mina C (Committee member) / Nelson, Brian C (Committee member) / Arizona State University (Publisher)
Created2019