Using video prompting to teach mathematics to adolescent students with LD

Abstract

BACKGROUND:

Research suggests that video-based interventions such as video modeling (VM) and video prompting (VP) assist students with severe/profound disabilities, such as autism and intellectual disabilities, to learn academic skills.

OBJECTIVE:

This study evaluates whether a VP intervention on a functional academic math skill would have similar effects for adolescent students with mild/moderate learning disabilities (LD).

METHODS:

A single subject multiple probe across subjects design was used. Five high school students (three female and two male) ages 16–17 viewed a video on an iPad to learn to calculate how much money an item would cost if a certain percentage of the price were deducted for a sale.

RESULTS:

A functional relation was found between use of the intervention and acquisition of the steps necessary to complete the calculation task. Three students maintained the skills, correctly answering most word problems on a post-test a month after completing the intervention.

CONCLUSIONS:

Results of this study suggest that VP can be effective in teaching mathematic procedures to students with disabilities. Implications for practice and further research are discussed.

Keywords

Learning disability LD math instruction video modeling video prompting iPad Common Core

1. Background

Practitioners are continually developing and implementing evidence-based practices to prepare individuals with learning disabilities (LD) to live productive and fulfilling lives. Basic proficiency in numeracy is a necessary skill to function successfully in both academic, daily living and employment contexts [1]. Unfortunately, a wide achievement gap is evident between the mathematics proficiency levels of individuals with LD and those of their peers without disabilities.

The National Assessment of Educational Progress conducted by the US Department of Education in 2015, commonly referred to as the Nation’s Report Card, found that only 8% of eighth grade students with disabilities (includes all disabilities) were at or above the proficient level in math, compared to 36% of students without disabilities [2]. With 92% of students with disabilities and 64% of those without disabilities performing below proficiency in math, interventions are critically needed. Due to current pressure for academic progress at federal, state, and local levels, public as well as professional emphasis on building student proficiency in mathematics has drastically increased [3]. Literature related to video modeling (VM) and video prompting (VP) has shown promise for increasing the percentage of students with and without disabilities who are proficient in mathematics in elementary and has the potential to do the same for high school-aged individuals. Studies on effective teaching of mathematic skills and instructional technology are explored in the following literature.

Many studies have focused on how to effectively teach math skills to students with learning disabilities [3]. For example, Jimenez and Courtade attempted to teach an algebraic equation to students with moderate developmental disabilities [4]. In a high school setting, teachers provided students with step-by-step explicit instruction on how to solve equations. Results showed that all three students were able to correctly solve the equation [4]. In another study, Calhoon and Fuchs used peer-assisted learning strategies, combined with curriculum-based measurements, to improve high school students’ math skills [5]. Math computation scores improved for the participants in the study. In dealing specifically with money, Cihak and Grim conducted a study in attempt to increase money awareness in children with autism [6]. Teachers were asked to provide instruction and modeling to teach a “counting-on” strategy in order to buy items at a store. In comparing baseline and intervention data, the results showed that all four students were able to successfully use the strategy [6].

Another intervention that has successfully been used to teach a variety of skills to students with disabilities is Video Modeling (VM). “Video modeling (VM) is a technique that involves demonstration of desired behaviors through video representation [7, p. 266].” VM has its theoretical roots in Albert Bandura’s social learning theory, which describes learning as a cognitive process that occurs through observation or direct instruction combined with operant conditioning or reinforcement [8]. Social learning theory serves as the theoretical foundation for observational learning and occurs when (a) the observer is attentive to the modeled behavior, (b) the behavior is retained or remembered by the observer, (c) the observer organizes and compartmentalizes the behavior, and (d) the observer is motivated to carry out the behavior [9]. Many behaviors are acquired through observational learning when people watch a model. Modeling has been effective in many settings for teaching desired behaviors to all individuals, including those with disabilities [10]; VM uses technology to expand its reach and influence specifically for students with disabilities. As an evidence-based practice, VM has shown positive effects for teaching students with disabilities academic, social, and life skills [11]. After a student has watched a video of a desired task in its entirety, he or she is expected to perform the target behavior from start to finish [12].

Although the term video modeling typically refers to an individual watching a video of another person (e.g., peer, teacher, paraeducator) modeling the behavior, a variety of VM strategies can be utilized to acquire new behavior [13]. Video self-modeling (VSM) occurs when a student watches a video of himself performing the desired behavior. Through editing, prompts are removed to make it seem as if the student can perform the behavior without assistance [7]. Another VM strategy is Point-of-view modeling (PVM). PVM has a student view a film showing how the desired behavior would look from the student’s perspective [14]. Findings from Cihak and Schrader suggest that, overall, there is not a functional difference when using participants themselves as a model compared to a peer [6]. VM can also be used through video prompting (VP) procedures, by which the individual is shown a video of a model performing a task-analyzed behavior in separate clips, one step at a time. After each step, the student is given an opportunity to perform the step before the next step is presented [15].

1.1 Educational application

When discussing the benefits of this evidence-based practice, VM and VP can be considered synonymous because of their similarities. Functional relations were previously established between VM interventions and attaining behavior and social skills. Blood et al. used VM as a model to teach an elementary-aged student with emotional disturbance that had off-task and disruptive behavior issues [16]. Disruptive behavior decreased, and correct classroom behavior increased once the VM intervention was introduced. Charlop et al. studied the effects VM with other as model had on socially appropriate expressions for elementary-aged students with autism spectrum disorder (ASD) [17]. The objective was to teach the students how to use acceptable verbal comments, intonation, and facial expressions. The VM researchers developed three different video scenarios for each student. The videos were three minutes long, on average, and had models depicting the various target behaviors within each scenario. After the students received the VM intervention, all students reached criterion levels of performance for all areas within 3–4 times of watching the video.

Researchers Decker and Buggey conducted a study to evaluate the effect a VM intervention would have on reading fluency for elementary-aged students with learning disabilities (LD) [18]. During intervention sessions, the student would watch the video of himself or a peer with acceptable reading fluency. After viewing the video, the student would be expected to read a passage at the participating student’s reading level. The dependent variable being observed was the number of words read correctly per minute. A multiple probe design across participants was used to assess VM effects on acquisition of reading fluency. Baseline results showed steady trends for all participants. After the reading fluency VM intervention was introduced, gains in words read correctly per minute were automatic. The researchers also evaluated what VM procedures were more effective, VSM or VM with other as model. The outcomes showed that both were effective at teaching reading fluency to the participants. A functional relation can be inferred from the findings.

In another study, Hitchcock, Prater, and Dowrick used VM to increase reading fluency for elementary-aged students with LD [19]. The first-grade students were given a short story passage at their reading level. The students were timed for one minute and correct words per minute were recorded. Baseline results for one of the students with LD ranged from between about 20 correct words read per minute to about 50 correct words read per minute with most sessions resulting in the 30 to 40 correct words read per minute range. After baseline, the students were introduced to the VSM intervention combined with tutoring where the student watched an edited video of himself reading fluently. During intervention phases, all students made increases in the number of words read correctly in a minute. For the previous student mentioned, an increase to around 90 words read correct per minute was observed. This study is further documentation of a functional relation between the independent variable, reading fluency, and the dependent variable, VSM.

Burton, Anderson, Prater, and Dyches used VSM to teach middle school-aged students with ASD and intellectual disabilities a functional math skill: estimating an amount of money it takes to purchase something and how much change to expect back from the purchase [20]. The student first watched an edited video of himself performing the target behavior, completing a math problem. The student could pause, fast-forward, or rewind the video as often as he chose in order to complete the problem. Baseline results were low. The students ranged from zero percent to a high of 30 percent correct. Within the first session of VSM being introduced, each student immediately performed the target behavior of at least 90 percent correct. Each student reached 100 percent correct by the second session. The results of this study indicated a functional relation between the dependent and independent variables.

Very few VM studies have addressed students with mild/moderate disabilities such as LD. According to the federal statute, Individuals with Disabilities Education Act [21], LD is defined as:

“a disorder in one or more of the basic psychological processes involved in understanding or in using language, spoken or written, which disorder may manifest itself in the imperfect ability to listen, think, speak, read, write, spell, or do mathematical calculations.”

O’Brien and Wood noted research is less extensive on applications of video modeling for students with learning disabilities [22]. Although extensive research has established the effectiveness of using VM for elementary-age children and some evidence supports using VM with middle school-age students, little research has been conducted using VM interventions with high school-age individuals.

1.2 Study purpose and research questions

The purpose of this study was to investigate the effects of a VP intervention on high school students with LD who were learning a functional math skill. Video-based intervention results would be expected to generalize across students with severe disabilities to students with LD, because VM and VP are universal principals founded in the social learning theory.

This study investigated the following questions:

1.
To what extent do adolescent students with LD use a VP intervention delivered via iPad to correctly complete the steps necessary for solving percent-cost word problems?
2.
After receiving the intervention, how well do adolescent students with LD independently solve percent-cost word problems correctly without using the VP instruction?
3.
How do the participants and teachers rate the VP intervention (social validity)?

2. Methods

2.1 Experimental design

A single subject multiple probe across participants design was used to determine whether there was a functional relation between the independent and dependent variable. Single-subject designs are a scientifically valid method of conducting intervention research where access to participants is limited such as when working with individuals with disabilities [23]. The independent variable was systematically introduced to different participants across different baselines. When a participant reached criterion (100% of the steps completed correctly for five consecutive sessions), the intervention was introduced to the next participant in random sequence. Baseline and intervention probes were conducted on participants as they started the intervention.

Data comparing baseline and intervention phases were visually analyzed for changes in level, trend, and variability. The objective of the research was to investigate a hypothesized functional relation between the dependent variable (percentage of steps completed correctly) and the independent variable (VP intervention) by observing changes. Kennedy explained, “If changes in the dependent variable occur only when the independent variable is introduced, then a functional relation is demonstrated [23, p. 152].”

2.2 Participants and setting

Three female and two male students, given the pseudonyms of Jeanie, Elaine, Clay, Krista, and Tucker, were selected based on predetermined criteria and teacher recommendation to participate in the study. Selection criteria included the following: (a) a specific learning disability classification as defined by the Individuals with Disabilities Education Act of 2004 and identified by the school district, (b) high school enrollment, (c) similar full-scale intelligence quotient (IQ) between standard scores of 85 and 115, (d) similar Broad Math score from the Woodcock-Johnson III: Tests of Achievement ${}^{\@setsize{\scriptsize}{8pt}{\viipt}{\@viipt}\textregistered}$ between standard scores of 75 and 85 [24], (e) at least one math improvement goal in the current Individualized Education Program (IEP), (f) access to a cell phone with a calculator, and (g) parental permission to participate in the study. All participants were identified LD by the school district based on a discrepancy model. For each student, classification was determined by the members of each student’s IEP team. Intellectual and cognitive evaluation was conducted by a school psychologist and academic assessment was conducted by a certified special education teacher. Students obtained a significant discrepancy of at least 74% between cognitive ability and academic achievement in mathematics problem solving. Additionally, all students were classified as having as LD. To protect the subjects involved in the study, Institutional Review Board approval was obtained prior to the start of the study.

All students attended the same suburban high school, enrollment of about 2000, located in the Western United States. Of the 2000 students, 8% of the population receives special education services. Students participated in a small-group resource math class every other day due to the school’s block scheduling system. Students received their core math instruction in a resource math class. The students did not receive percent of costs instruction in the resource math class. In addition, the students did not receive any instruction on any aspect of percentages from the time the school year began to the conclusion of the study. The math resource teachers reported that each of the participating students had difficulty understanding math concepts when involved in whole group instruction, small group instruction, and independent practice. All participant selection criteria came from existing data. No new assessment was given to determine eligibility for the study. More information about each student follows.

2.2.1 Jeanie

Jeanie was a 16-year-old Grade 11 student. On the Woodcock-Johnson III: Tests of Cognitive Abilities ${}^{\@setsize{\scriptsize}{8pt}{\viipt}{\@viipt}\textregistered}$ [25], Jeanie scored in the average range with an IQ standard score equivalent of 97. Her academic testing suggested she would benefit from specialized math instruction, as her Broad Math standard score was 78, which is in the below average range. Jeanie also had a math improvement goal in her IEP. Her most recent discrepancy score was 93%, and she was classified LD at age six.

2.2.2 Elaine

At the time of the study, Elaine was a 16-year-old Grade 11 student. Elaine’s cognitive scores indicated an average IQ standard score equivalent of 103. According to the Woodcock-Johnson III: Tests of Achievement ${}^{\@setsize{\scriptsize}{8pt}{\viipt}{\@viipt}\textregistered}$ [24], Elaine had below average math skills, with a standard score of 84 in Broad Math. Elaine had a math improvement goal in her IEP. She had a discrepancy score of 96% and was classified LD at 11 years old.

2.2.3 Clay

Clay was a 16-year-old Grade 11 student. Information gathered from Clay’s cognitive testing showed a full-scale IQ standard score of 87, a low average score but within the first standard deviation. Like other participants, Clay scored below average in Broad Math, with a score of 81. He had a math improvement goal on his IEP. Clay obtained an 88% discrepancy and was classified LD at age six.

2.2.4 Krista

Krista was a 17-year-old Grade 11 student. Her cognitive testing scores showed an IQ standard score of 96, which is within the average range. A Broad Math score was not found in Krista’s testing history, but her Math Reasoning score was 82. Krista had a math goal on her IEP. She had 99% discrepancy and was classified LD at age six.

2.2.5 Tucker

Tucker was a 16-year-old Grade 11 student throughout the research. Tucker’s full-scale IQ standard score of 86 was within the first standard deviation. On the Woodcock-Johnson III: Tests of Achievement ${}^{\@setsize{\scriptsize}{8pt}{\viipt}{\@viipt}\textregistered}$ [24], Tucker’s score was in the below average range, with a Broad Math standard score of 77. Tucker also had an improvement goal in math listed in his IEP, his discrepancy was 74%, and he was classified LD at age five.

2.3 Task selection and materials

A VP intervention was recorded with a model and PVM techniques to teach a percent-cost skill to five students. Common Core State Standards are math and English grade level learning targets that were developed to prepare students for college and careers upon completing high school. These standards drive curriculum and assessment in most states. Specifically, this study addressed CCSS.MATH.CONTENT.7.RP.A.3, which reads, “Use proportional relationships to solve multistep ratio and percent problems. Examples: simple interest, tax, markups and markdowns, gratuities and commissions, fees, percent increase and decrease, percent error [26].” Although this is a Grade 7 skill, students must be able to work with percentages to reach higher level high school mathematics Common Core standards such as Standard F-IF.8.b., F-LE.1.c., and S-ID.4 (National Governors Association, 2010) [27]. With the finding that most secondary level students with LD perform three grade levels below their peers in academic subjects, the researchers considered this particular Common Core standard appropriate for high school-age students with LD.

The selected task was based on CCSS.MATH. CONTENT.7.RP.A.3. and consisted of solving percent-cost word problems. A task analysis, consisting of the steps necessary to complete the problem correctly, was developed following the criteria set forth by Cooper, Heron, and Heward [28]. After completing the task analysis, it was verified for accuracy by a secondary math teacher.

The selection of the model for the intervention video considered previous research that demonstrated no functional difference between using self or a peer as the model, and that both were effective [6]. The current study used a peer as a model. The model in the video was similar in age and appearance, so the participants were able to relate to them. Videos of each step were recorded using an iPad 2, then edited and put together using iMovie 2011 (version 9.0.9). The edited video was uploaded to the iPad VideoTote application [29], and segmented into video steps for VP instruction. A single VP video, separated into clips for each step of the task analysis, was used throughout the entire study, showing a model demonstrating how to successfully complete a percent-cost word problem. For example: “A shirt is normally $19.99. It is on sale for 30% off. What is the sale price of the shirt?”

At the beginning of each session, the student received a percent-cost word problem similar in wording and structure to, but not the exact same as, the problem solved in the VP video. The following established a framework for each question: “A ____ is normally $_____. It is on sale for ____% off. What is the sale price of the _____?” The only differences between questions included the item on sale, the sale price, and the percent the item was on sale for. The items used in the questions were common items the students were familiar with but did not necessarily have a relationship to one another. Examples of items included, but were not limited to, a bicycle, pizza, coat, backpack, book, and concert ticket. Researchers had developed 30 word problems and randomized the problems sequence for all participants. Students had a pencil and access to a calculator for baseline sessions. Students used their own phones during intervention trials (any phone with calculator access).

2.4 Dependent measure and data collection

The dependent variable in the study was student acquisition of the skills necessary to complete the math word problem. Data collection occurred through direct observation of the students. The task analysis was used to collect data during all sessions. Percentage correct was calculated by dividing the number of steps completed correctly by the total number of steps in the task analysis. Participating students received the iPad VP instruction only during intervention. They could watch the video segment as many times as needed before completing the step without having the step marked as incorrect.

Data were also collected on the number of percent-cost word problems completed correctly. Data on this variable were collected through pre- and post-tests. The pre-test consisted of five percent-cost word problems written in the same style as the one used in the VP video. The post-test was identical to the pre-test, containing the same problems. A percentage correct was determined by how many questions were answered correctly divided by five.

Two sessions were held each data collection day, with at least 30 minutes between sessions. Because of the block scheduling, data collection occurred either two or three times per week. The students were pulled out of their math class into a quiet room in the school. Intervention sessions lasted approximately 10 to 15 minutes. No rewards were given for participating in the study.

2.5 Procedures

2.5.1 Pre-assessment

Before participants started baseline, each was required to complete a pre-assessment phase that consisted of demonstrating iPad competency, understanding of rounding up numbers, and completing a pre-test. Participants were considered knowledgeable if they could navigate basic features of the iPad and perform the required actions when asked (e.g., access a given application, play/pause videos, turn volume up/down). Knowledge was assessed with a checklist on which students needed to score 100% in order to participate in the study.

To make solving the percent-cost word problems accessible for participants, the researchers determined students would benefit from being able to round numbers of cents up to the next highest dollar. (Rounding up could potentially allow a little bit of room during future real-word applications involving tax.) All prices involved with the study included between 50 and 99 cents over the number of dollars. In addition, no number exceeded 300. As students would need prior knowledge of rounding up in order to participate in the study, researchers assessed this knowledge by having students fill out a worksheet consisting of 10 questions requiring them to round a price up to the next highest dollar. Students had to score 100% to continue with the study.

An additional pre-assessment measure was a pre-test to evaluate whether students already had the skills necessary to correctly answer percent-cost word problems. Being able to answer the questions would indicate that a student did not need the VP intervention. Students were allowed access to all items needed to complete the five-word problems on the pre-test (i.e., pencil, eraser, and calculator) but no iPad. A student who answered at least one question correctly would not have been considered for further participation in the study; however, none of the students were able to solve any problem. The pre-test was graded as either answering a question completely correct or completely incorrect.

2.5.2 Baseline

After meeting pre-assessment standards, a participant moved into baseline. During this phase, the individual was taken out of the resource math class into a quiet room and given one of the percent-cost word problems randomly selected. With access to a pencil, eraser, and calculator, the student was told to solve the problem. The task analysis was used to evaluate the percentage of steps performed correctly (see Table 1). Once a participant established a stable baseline with low variability, set at no more than 10% difference among all baseline points for at least five consecutive data points, the participant was eligible to move into the intervention phase. Baseline probes were conducted with all participants who had not yet moved into intervention whenever a new participant entered intervention.

Table 1
Task analysis

Step	Task analysis
1	Access calculator on mobile device.
2	Type in rounded up original cost of item.
3	Hit “multiply” button.
4	Type in percentage in decimal form.
5	Hit “equals” button.
6	Clear the screen.
7	Type in rounded-up original cost of item.
8	Subtract previous calculation from rounded up original
	cost.
9	Hit “equals” button.
10	Verbally tell the teacher the correct final sale price of the
	item.

2.5.3 Intervention

Participants were randomly selected after completing baseline phase to move into the intervention phase one participant at a time. Participants were pulled out of their resource math class and brought to one of the school’s unused conference rooms to receive the intervention. Because only one participant at a time received the intervention, participants never received the intervention in the same room at the same time, and they were not able to speak to each other when involved in the intervention. The VP intervention video was the same for all students.

Before moving into intervention, the participant was taught how to find the correct application and which video to choose on the iPad. The participant was then told that the video would pause at different steps of the skill, and after completing each step, he or she would need to press anywhere in the middle of the screen to move to the next step until the video was completely finished.

During the intervention, participants had access to a pencil, eraser, calculator, and the iPad with the VP video. The researcher read the following instructions: “You will now watch a video that will help you learn a skill. The video will pause after each step in the skill. When it pauses, you will need to complete the step you just watched. You can watch the video segment as many times as needed by pressing the back button once at the bottom of the screen. After you complete the step, press anywhere in the middle of the screen to continue to the next step. You will continue doing this until you learn the skill.” After receiving the instructions, the participant was given one of the percent-cost word problems randomly chosen and told to solve the problem using the VP intervention on the iPad. The task analysis data sheet based on the steps identified in Table 1 was filled out as the participant worked through the word problem. The participant was required to reach criterion at 100% for at least five consecutive sessions. After a participant reached criterion, the next randomly selected participant was able to move into the intervention phase.

If the participant needed an additional prompt to start the VP intervention after receiving the word problem, a verbal prompt could be given. If the participant did not know what to do when the video paused, after at least five seconds of wait time, the student would be prompted, “Now you do the step you saw in the video.” These reminders were not counted against the participant’s score.

2.5.4 Post-test

A month after a participant had reached criterion in the intervention phase, he or she was given a post-test, preceded by a probe with the VP intervention the day before. This final assessment was exactly the same as the pre-test, with the same procedures and problems. The post-tests were graded as either answering a question completely correct or completely incorrect. The post-test data were compared with the pre-test results to determine if the VP intervention had taught adolescent students with LD how to independently obtain the correct answer for percent-cost word problems when the VP intervention was not available to them.

Although the main reason post-assessment results were reported was to determine whether the student could or could not perform the skill, the post-tests were also scored according to the task analysis to determine if the steps were maintained over time. However, scoring procedures differed slightly from the intervention phase. Post-assessments could be considered correct if a participant had switched the order of some steps: for example, rounding up the cost of the original item and then calculating the percentage in decimal form before accessing the calculator. Also, instead of raising a hand to offer an answer to a teacher, a participant could just write the final answer on the worksheet.

2.6 Interobserver agreement and treatment fidelity

An observer was present to record data during all sessions of the study. The first author, a classroom teacher, took the role of primary researcher. With consent, the teacher video recorded the participants during baseline and intervention phases. To determine interobserver agreement, a second observer watched the recorded videos and collected observational data for 50% of all sessions during baseline and intervention phases. The first observer’s results were validated by an interval agreement approach, which requires each step in the task to be recorded as either completed independently or not completed independently. If both observers recorded an item as completed, it was marked as an agreement. If both recorded an item as not completed, it was marked as an agreement. Any variation was marked as a disagreement. Inter-observer agreement would be found by dividing the number of agreements by the sum of the number of agreements and number of disagreements and multiplying by 100 to get a percentage of interobserver agreement for each session [23]. Sessions used for interobserver agreement were then averaged to obtain an overall interobserver agreement percentage. Using this approach, interobserver agreement was reported at 100%.

Treatment fidelity measures were in place to ensure the researchers administered all areas of the study consistently and correctly across all participants. The researchers completed a fidelity checklist for all pre-assessment/post-assessment and baseline phases. A detailed fidelity checklist was completed for at least 50% of all intervention sessions for each participant. Fidelity checklists were also completed for all baseline and intervention probes and were calculated to be 100%.

2.7 Social validity

A subjective measure of social validity is also important to determine how well-received the intervention is by important stakeholders such as the participating students and teachers. Social validity was assessed using a multiple-choice questionnaire given to the direct consumers – the participants involved with the research. The questions asked represented acceptance and understanding of the goal, method, and outcomes of the independent variable [30]. The questionnaire also requested the participating students’ thoughts, feelings, and perceptions about their behavior achievement before and after the intervention, personal view on the effectiveness of the intervention, and likes and dislikes about VP. Each participant filled out the social validity questionnaire just after completing the post-test. The researcher read the questions aloud to the participant as he or she filled out the form, which required about 10 minutes to complete. Each participant’s answers were analyzed and evaluated to establish the overall perceived effects of the intervention.

The participants’ math teachers also answered a similar social validity questionnaire. The form was given in a multiple-choice format with space below each question to write notes or comments if the participant or teacher desired. Social Validity results are discussed below.

3. Results

A multiple probe across five participants design was used to evaluate effects of a VP intervention via iPad on percent-cost math performance of adolescent students with LD. Data analysis shows a functional relation between VP and student learning of the steps required to solve percent-cost word problems for all five participants. All participants completed zero of the 10 steps correctly during all sessions in baseline. After the intervention was introduced, four of the five participants completed 100% of the steps correctly during the first session. The largest number of sessions required by a participant to reach criterion at 100% for five consecutive sessions was 13. Figure 1 shows the effect of the VP instruction on the percentage of steps completed correctly.

Figure 1.

Graph of intervention results regarding video prompting intervention for five high school students with LD learning a functional math skill.

3.1 Results of five participants

In regards to research question one the study provides evidence that VP instruction helped some participants acquire the skills to complete the percent-cost word problems correctly. All five participants scored 0% correct in the pre-test. Two participants completed the post-test with 100% accuracy, one participant with 80% accuracy, and two participants with 0% accuracy. Additional evidence has shown that the two participants who scored 0% were still acquiring the skill.

3.1.1 Task completion with video prompting

During baseline, Jeanie scored 0% for all five trials before entering the intervention phase. Baseline was stable with no variability. When the VP intervention was introduced, Jeanie scored 100% of steps completed correctly. She quickly reached criterion with five consecutive data points at 100%. An additional four intervention probes were conducted before she took the post-test. During one intervention probe, Jeanie showed a slight downward trend, but returned to 100% during the next probe session. The mean percentage of steps performed correctly during the intervention phase (including probes) was 98%.

Elaine scored 0% of steps correct throughout the baseline phase; data were stable with no variability. When she transitioned to the intervention phase, she scored 100% of the steps correct during the first session. She scored 90% in her third intervention session but scored 100% for all other trials. Her mean percentage of steps performed correctly during the intervention phase was 99%.

Clay scored 0% for all baseline sessions. During his first intervention trial, he performed 80% of the steps correctly. After that, he reached criterion at 100%, showing slight variability when he scored 90% on an intervention probe. Session 21 was removed from the data because he hid what he was doing on the calculator from the researcher, who was thus unable to determine whether Clay was performing the steps correctly. Session 22 was not counted toward the five consecutive data points required for criterion because the researcher could not determine the percentage of steps completed correctly for the session that was removed. Clay’s mean percentage of steps performed correctly during the intervention phase was 97%.

Krista had a steady baseline with no variability at 0% for all sessions. She started the intervention phase with 100% but then experienced some variability with scores of 70%, 80%, and 90% between scores of 100%. She reached criterion after 13 sessions. Her mean percentage of steps performed correctly during intervention was 94%.

Tucker had a steady score of 0% for all baseline sessions including probes. He had the most significant change among the participants, from all baseline data at 0% to all intervention data at 100%. No variability or trend changes occurred once Tucker started intervention. The mean percentage of steps solved correctly during intervention was 100%.

3.1.2 Post-test

To answer research question two a post-test was given without the intervention a month after reaching criterion, Jeanie used all the steps necessary for four of the five problems given. For one of the problems, she completed 80% of the steps correctly, but gave an incorrect final answer. Thus, she scored 80% on the post-test.

Elaine used all the steps necessary for completing all five of the word problems on the post-test for a score of 100% correct.

Although Clay scored 0% correct on the post-test, the percentage of steps solved correctly suggests that this skill is still being developed. For the first question, Clay performed 100% of the steps correctly, but not in the right sequence. At one point he performed alternative calculations and came out with an incorrect answer. For question two, he scored 90% steps completed correctly. For questions three through five, he scored 70% steps completed correctly.

A month after reaching criterion during intervention, Krista took the post-test. She used 80% of the steps correctly for all five questions. Because she missed two key steps, her final answers to the problems were incorrect; thus, she scored 0% on the post-test. Krista seems to be still developing the target skill.

Tucker used all the steps correctly to complete the word problems on the post-test, scoring 100%.

3.2 Social validity

In response to the final research question three of the five participants reported they enjoyed learning by watching a video on an iPad. One question assessed the participants’ acceptance of an integral component of the VP intervention: having the video pause between steps. The question read, “Did you like having the video paused after each step to give you a chance to complete the step before going on?” Three participants reported, “Yes,” with one adding in the comments section, “The short pause for ‘Now press the equals button,’ was unnecessary.” Two participants answered that pausing the video between steps did not matter to them. One of these participants added in the comments section, “At first it was helpful.” When asked if the participants would like to watch more videos teaching a skill in class, all five said they would prefer a combination of videos and teachers instructing them.

The three teachers who taught the participating students’ core resource math instruction also completed a social validity questionnaire. Two teachers reported it seemed the participants enjoyed the video-based intervention. (The other teacher did not answer this question.) All three teachers reported that if they were to use a video-based intervention for their students, they felt they would need access to custom-made, ready-to-go videos to help them succeed with implementation.

4. Conclusions

The purpose of this research was to determine if a VP intervention for a mathematics skill via an iPad would help high-school students with LD acquire the steps to solving percent-cost word problems. Data from the study supported a functional relation between the use of the intervention and the percentage of steps completed correctly. This functional relation was observed, as the dependent variable changed only when the VP intervention had been introduced to the participating students.

The results of this study were similar to other VP studies targeting individuals with LD [19]. Although this research was one of the first VP studies on adolescents with LD, the functional relation established in this study corroborates other VM research specific to students with LD [18, 22]. In addition, the results support existing research on positive effects iPad delivery can have on student skill acquisition [31, 32, 33] and specifically on student math skill acquisition [20].

This research also aimed at answering the question of whether the intervention helped the participants answer the specific percent-cost word problems correctly. Although two participants did not score considerably higher in answering all the percentage word problems correctly on the post-test, the participants who scored 0% on the post-test still did follow most of the steps required to solve the word problems correctly. Essentially, while two of the participants did not increase in the number of problems completed correctly, they were able to significantly increase the percentage of steps completed correctly for most word problems on the post-test. This evidence suggests that future studies be aimed at helping students not only complete the correct steps but also retain the information over time.

Findings from the study suggest that VP was promising in teaching math related concepts for high-school students with LD. It is hypothesized that the significant immediate gains made were due to several factors. The first is that traditional math instruction is delivered in group settings of mixed abilities. This intervention delivered differentiated instruction and allowed the student to review each step as many times as needed. This ability to re-watch the video may be tied to the gains made. A second hypothesis is that the VP videos act as a filter, removing unnecessary audio and environmental distractions present during traditional face-to-face instruction. The removal of these distractions could increase the ability of the students to pay attention to the presented information. Future study is needed in both areas.

An additional conclusion is that while the results demonstrated acquisition of the target skill in a school-based environment no data was collected on generalization in real world situations outside of a school setting. It should be noted that percent-cost problems can emerge in many different ways, structure and wording in real life situations. Structured and guided approaches have proven effective for some learners and especially learners in ASD such as the current study. Current research and literature often successfully leverage these approaches to increase community and social engagement for individuals with ASD.

Results of the current study are useful in extending the current VM literature in various ways. This is the first study to evaluate the effects of a VP intervention delivered via iPad to adolescent students with LD who are learning an academic skill linked to the Common Core State Standards. This research also adds to the existing VM literature on students with mild/moderate disabilities and to VP literature particularly.

Much of the existing literature on VM involves video-based interventions for students in elementary school settings. The research conducted by the researchers in the current study delivered a socially valid VP intervention to students in high school. As one of the first of its kind, this research provides literature that serves as a foundation for video-based intervention strategies for students in high school.

4.1 Limitations

This study would have been stronger if it had included a maintenance phase. Initially the researchers had planned to use the first question answered on the post-test as maintenance data. However, the delivery of the five post-test questions on one worksheet was different from the delivery of one problem on a single worksheet during baseline and intervention. Because of this departure from the accustomed format of delivery, the researchers decided not to include the data as maintenance, although they would have liked to assess whether learning the steps for solving percent-cost word problems were retained over time. The findings from the post-test are still valuable and are included in the Results section of this article.

Limitations existed within the word problems. Researchers used only prices that ended in 50 cents through 99 cents, so it would be easy for the students to round up. However, in studies targeted to train students to use this skill in real-world application, having prices ending in 0 through 99 cents would be beneficial. A limitation also existed in the nature of the data collected from the word problems. The pre and post-tests collect data on correct answer of the problems, rather than how well they completed steps to solve the problems. An additional limitation includes only using one word problem per probe. Additional problems in a session may have warranted more exposure to the intervention, the lack of which may have contributed to Clay and Krista’s variable performance on the post-test.

Another limitation was that the current study did not account for generalizability and sustainability of the math skill. While the participants were all able to demonstrate acquisition of the skill there was no additional data collected to see if the skill would generalize to other settings. This could have been remedied by including an additional phase requiring the participants to complete the skill in a real world setting.

A final limitation was that the first author assumed the roles of both teacher and researcher. It appeared this might have affected how seriously some participants received the intervention. For example, during one of his trials, Clay was joking around and covering his calculator so the researcher could not see, and the trial was removed from the study. Having a primary researcher who was unfamiliar to the students might have avoided this problem.

4.2 Suggestions for future research

Replication of this study would help to validate and strengthen the answers to the research questions. In addition, this study could be used to answer other research questions, such as inquiry about engagement and on-task behavior when using video-based instruction compared to teacher-led instruction. These results could also be used to contrast the effectiveness of a VM intervention vs a VP intervention for adolescent students with LD. Additional research is also needed on the effects of VP on other skills included in the Common Core State Standards and on VP use in inclusive classroom settings.

Teachers and families of adolescents with LD would find it highly useful to determine what the results of the current study might imply about real-world application. For example, after learning via these methods, do students generalize the skills to purchase items of interest that are marked a percentage off? Future research might also note the number of additional video prompts that are needed to complete the task or how often the students watched each clip. Other possible follow ups might include fading the prompts for the VP intervention or combining VM with teacher-led instruction. The latter suggestion is based on the results and comments from the social validity questionnaire.

4.3 Implications for practice

This research suggests that technology, specifically an iPad, can be used to enhance instruction and implement intervention to improve academic performance of adolescent students with LD. Visual imagery is a validated method for teaching students with LD [18]. This makes VM practices, including VP, useful instructional tools for many students with LD. It is also hypothesized that the visual representation of the steps for solving math problems may benefit all learners not just those with LD.

Practitioners can use this research as a guide in creating other videos for math instruction to their students with LD. Videos can be made once and shown as many times as needed to students who might need additional instruction independently, allowing teachers to complete other responsibilities. Video development requires only the time necessary to complete the instructional task once and then addition time to edit with voice-over directions or to separate the video into clips, making this intervention easily accessible to practitioners.

Once teachers have the materials they need and have taught students how to access the VM intervention, students can independently participate with less teacher supervision or assistance. While students are using the iPad, teachers can use the time to work with other students in small groups or one- on-one. A VM intervention is also useful in promoting students’ independence, giving them opportunities to be accountable for their own learning [34]. These are essential skills for students to obtain, especially adolescents preparing for adulthood.

Author contributions

CONCEPTION: Sean Edwards, Ryan Kellems, Gordon Gibb and Betty Ashbaker

PERFORMANCE OF WORK: Sean Edwards

INTERPRETATION OR ANALYSIS OF DATA: Sean Edwards and Ryan Kellems

PREPARATION OF THE MANUSCRIPT: Sean Edwards, Ryan Kellems, Kaitlyn Frandsen and Alex Wheatley

REVISION FOR IMPORTANT INTELLECTUAL CONTENT: Sean Edwards, Ryan Kellems, Kaitlyn Frandsen and Alex Wheatley

SUPERVISION: Ryan Kellems, Gordon Gibb and Betty Ashbaker

Ethical considerations

This study approved by the Institutional Review Board at Brigham Young University (F 14189) and conducted in 2015. Informed consent was obtained from all participants.

Footnotes

Conflict of interest

The authors have no conflicts of interest to report.

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