An Independent Virtual Mathematics Program for Middle-Grades Learners: Using Screencasts to Support Students’ Mathematical Knowledge and Motivation

Many different interventions have supported grade-level learners who do not attain the desired mathematics achievement levels to close the achievement gap. While many factors contribute to student success, research-based interventions utilizing independent virtual learning environments benefit student learning (Slavin et al., 2013). Following its success in the higher education setting, virtual learning also became more critical in the field of K–12 education (Huh & Reigeluth, 2018). Recently, due to global disruption from the COVID-19 pandemic, online learning (also described as emergency remote learning) occurred as the prominent alternative teaching-learning process, requiring teachers to adapt themselves to this new normality. With the pandemic, K–12 teachers familiarized themselves with the concepts of asynchronous, synchronous, and blended instructional formats and learned to use various teaching strategies, such as videoconferencing, gamification, peer-teaching, and open discussions in technology-enhanced online K–12 environments (Krouska et al., 2022; Polly et al., 2021; Shamir-Inbal & Blau, 2021).

Researchers have been exploring the variables resulting in the success of virtual learning in K–12 settings and students’ understanding of concepts learned with online tools (Causey, 2014; Gulley, 2009). Gulley (2009) found that computer-based education (CBE), using video clips and paper-based assignments at school, was an effective intervention for middle-grade mathematics. CBE allowed the mathematics teacher more time to work with students in smaller groups and one-on-one than in the traditional classroom setting. In addition, students in the CBE classroom outperformed students in the traditional education setting. Flipped Classroom Models (FCM) are more effective in improving students’ academic performance, especially in elementary and middle grades, compared to traditional instructional models (Güler et al., 2023). Bergmann and Sams (2012) found that the FCM increased students’ mathematical understanding and success due to the increased practice time in class with their peers and the teacher. In this FCM, the students viewed screencasts at home before attending the in-person class, where the teacher spent less than ten minutes fielding questions from the screencast and then used the majority of the in-person class time completing practice problems (Bergmann & Sams, 2012). Wei et al. (2020) studied the effect of FCM on middle school students’ mathematics learning performance in China. In this study, for five weeks, students in the experimental group used an online learning platform to watch assigned video lectures and completed the corresponding assignments before the in-person mathematics class. The researchers’ statistical analyses revealed that students in the experimental group significantly improved their mathematics performance compared to the control group who went through the same content without FCM. Students taking notes while viewing the instructional videos and teachers’ questioning approach during the in-person classes could be the moderating factors in students’ increased achievement with FCM.

A common form of video instruction that has been used in the FCM is screencasting, which is a form of multimedia that consists of interactive writing and teaching with voice-over on the screen and slides (Snyder et al., 2014). Screencasting provides an effective supplemental learning tool and thereby has many positive effects on learners, such as increasing motivation, engagement, and student satisfaction and reducing course-related anxiety (Evans, 2008; Hew, 2009; McKinney et al., 2009). Screencasting has been used as a tool for flipped classrooms for different subject matter instruction and various grade levels (Kwon et al., 2018; Richards, 2012; Snead et al., 2023; Snyder et al., 2014). Snyder et al., (2014) used screencasting for ninth grade history classes to increase student engagement, improve students’ technological skills, and meet the needs of students with special needs. Kwon et al. (2018), on the other hand, used screencasts as a data collection tool to explore ninth grade students’ inquiry behaviors in a problem-based biology class.

Snead et al., (2023) utilized student-created screencasts to support 10^th grade students’ peer learning for advanced mathematics topics. A similar approach was used by Larsen and McCormick (2020) with second graders, where students worked on arithmetic problems individually and shared with their classmates through screencasting. Such use of screencasting allowed teachers to provide students with a meaningful struggle and set high expectations for the students. Students in this class more frequently engaged in mathematical discourse and justifications of their reasoning. Bjerknes et al. (2024) recently studied the use of screencasts for teacher feedback and its impact on middle-grade and high school students’ mathematics learning. The mathematics teachers in this study provided their feedback with screencasts of themselves evaluating students’ mathematics assessments and suggesting ways to improve their performance on the next test. Most students indicated they prefer video feedback about their test instead of written feedback, as the video motivates students more to study and understand the mathematical content. In another study, Richards (2012) found that middle-school students enjoyed learning mathematics from screencasting as they could take their learning into their own hands and show it using a comfortable strategy. Nonetheless, the literature is limited in its use of screencasts as an intervention for middle-grade students’ gains in mathematical knowledge and motivation. This study fills this gap in the literature.

Middle school years represent a distinct period for early adolescence, which differs from children’s development during the elementary and secondary school years. During these years, young adolescents go through physical, cognitive, cultural, and social-emotional developments (Caskey & Anfara, 2014). These changes also determine students’ thinking about schooling, which can result in a decline in their academic motivation (Roeser et al., 1998). Students in middle grades start reasoning more abstractly and reflectively about complex concepts and engage with intellectual challenges (cognitive), connect what they learn to their social lives (social-emotional), and develop self-awareness and identity (cultural) (Howell et al., 2011; Manning, 2002). Accordingly, most middle school curricula, with attention to students’ cognitive development, require that they engage in formal operational thinking. However, researchers also argue that only a third of middle-grade students can practice formal operations with abstract concepts, which underlines the role middle-grade teachers play in helping students in this age group reason more abstractly and logically (Brown & Canniff, 2007).

Roeser et al. (1998) suggested that middle-grade teachers should support early adolescents’ developmental needs in terms of three concepts: competence (by setting up specific expectations and goals), autonomy (by showing the relevance of content for their lives), and relationships (by being inclusively supportive considering their diverse backgrounds). To follow these suggestions, teachers are also recommended to practice learner-centered, developmentally responsive pedagogies that engage students in scaffolded critical thinking and individualized learning (Brown & Canniff, 2007; Howell et al., 2011). When planning virtual learning experiences, educators need to pay attention to young adolescents’ needs and find ways to provide learner-centered, developmentally responsive opportunities.

Asim et al., (2020) stressed that teaching middle-grade students online requires educators to have in-depth content knowledge and an understanding of the background and needs of their students. The design of the online experience needs to be built for students’ academic readiness for the content presented and their interest and motivation in learning the content online. With the pandemic, many middle-grade educators found themselves at the center of thinking about these necessities when they were tasked to convert their in-person teaching practices and materials to online teaching and learning. Whereas meeting middle-grade students’ developmental needs can pose a challenge in person, teachers face a more significant challenge in an online environment to be able to meet the social and social-emotional developmental needs of students. Based on their literature review, Vawter and McMurtrie (2022) recommended the following to meet the developmental needs of young adolescents during online teaching: personalizing and individualizing the learning experience, providing clear structure in students’ online learning with clear expectations and guidance, offering ongoing support with online feedback about their engagement and performance, practicing flexibility (in terms what to learn and when to learn), and teaching resilience in reaching their learning goals. We believe that teaching students’ resilience can only be achieved by finding ways to motivate them to learn content in online environments.

Self-determination theory (SDT) was developed by Deci and Ryan (1985) as a way to explain human behavior. SDT is fluid and continually evolves as time progresses and new research is conducted. However, SDT always uses certain aspects of motivation to explain human behavior (Deci & Ryan, 1985), such as educational-related behaviors. In their educational research, Hsu-Ching et al. (2019) view SDT as a frame that connects students’ developmental needs, their well-being, and their motivation to learn and achieve positive outcomes. Hsu-Ching et al., consider autonomy (i.e., a sense of agency), competence (i.e., confidence to complete a task), and relatedness (i.e., feeling socially connected with others) necessary for someone to achieve self-determination. Applying SDT in education promotes students’ value, interest, and motivation in learning and education, as well as confidence in their skills (Deci et al., 1991).

Deci and Ryan (1985) explored SDT and the roles of both intrinsic and extrinsic motivation in various amounts based on the student’s autonomy (Deci & Ryan, 1985). As motivation is the key to success in education, motivational regulation is an essential factor in student achievement (Eckerlein et al., 2019). To make sense of motivation as a construct, one must differentiate extrinsic from intrinsic motivation. Extrinsic motivation stems from external sources of learning, such as rewards and praise (Lohbeck, 2018). For middle-grade students, extrinsic motivation for learning was related to task features, group arrangements, and characteristics of teacher interactions (Wilkie & Sullivan, 2018).

In the revised version of SDT, extrinsic motivation has four subtypes: external regulation (i.e., behaviors mainly influenced by rewards and punishments), introjection (i.e., behaviors regulated by internal rewards or to avoid anxiety or shame), identification (i.e., consciously high willingness to act), and integration (i.e., valuing the activity congruent with other core interests) (Ryan & Deci, 2020). According to this new conceptualization, humans are extrinsically motivated for specific activities, which might have different levels of internalization and value of the activity for the self; these levels determine one’s extrinsic motivation category.

Extrinsic motivation is short-lived and has only been documented to predict short-term improvements in mathematics achievement for K–12 students (Murayama et al., 2013). Intrinsic motivation (as a component of SDT) is defined as the underlying source of energy that drives behavior for no external reward but only due to the personal interest in and engagement with the task itself (Ryan & Deci, 2006; Schunk, 2012). SDT explains that humans are motivated when they feel a sense of agency and have their intrinsic needs met. According to Ryan and Deci (2020), people can be extrinsically motivated to engage in an activity without the existence of external reward or punishment but due to the internal value they attribute to the activity (that does not have to be found personally interesting) (i.e., integration). On the other hand, people are intrinsically motivated to engage in an activity when they find it personally fun and interesting. Ryan and Deciadded a new category of motivation under SDT: amotivation, which is defined as having a lack of interest, self-competence, and value for the activity. Amotivation, a negative predictor of student learning and cognitive engagement, is unfortunately common in the classroom (Ryan & Deci, 2020).

Research has demonstrated numerous benefits of incorporating SDT principles into teaching across the K–12 setting (Atit et al., 2020; Wilkie & Sullivan, 2018). Wilkie and Sullivan (2018) also found that middle-grade students’ intrinsic motivation to learn mathematics was related to their self-confidence, self-concept, and ability to learn more efficiently. Therefore, mathematics educators must use pedagogical strategies that improve students’ intrinsic motivation toward learning during mathematics instruction. Atit et al. (2020) later showed that students’ extrinsic and intrinsic motivation played a role in the success of seventh graders on a mathematics standardized assessment. Additionally, intrinsic motivation (i.e., the internal desire to complete a task) is the most important motivation for overall student achievement (Taylor et al., 2014). The researchers recommend that future studies aim to differentiate the role between intrinsic and extrinsic motivation better to understand the impact of motivation on student success (Atit et al., 2020).

New research is also beginning to investigate connections between SDT, intrinsic motivation, and online learning environments (Hsu-Ching et al., 2019; Sergis et al., 2018). While Atit et al. (2020) did not examine students’ motivation concerning virtual learning or screencasting, their results provide insights for this present study and suggest that researchers uncover the balance between intrinsic and extrinsic motivation to maximize student success with virtual learning in middle-grades mathematics. In our study, we similarly assumed that students would need to be intrinsically motivated for the use of screen-casts and online learning opportunities to take effect in their mathematics achievement—especially since the use of screencasts requires students to become independent learners, take responsibility for getting access to technology, and grasp the mathematical content independently. Therefore, we hypothesized that the most intrinsically motivated students would benefit from independent online learning environments.

The relationship between middle-grade students’ motivation within virtual learning environments remains largely unexplored. Jain (2019) is one of the few studies exploring the impact of flipped instruction on middle-grade students’ motivation to learn mathematics. In this study, Jain found no statistical difference between middle-grade students’ intrinsic or extrinsic motivation for learning mathematics. The author credited their results in students’ motivation and their departure from literature to the possibility of the culture that prioritizes grades, the teacher’s knowledge, and the short one-week implementation. Jain’s study only investigated the influence of one week of online instruction. However, our study contributes to the literature by examining the effect of a 12-week VIVMP on middle-grade students’ motivation to learn mathematics. The following research questions guided our study to fill the gap in the literature: (1) How does a 12-week VIVMP impact middle-grade students’ mathematical knowledge? (2) To what extent does middle-grade students’ motivation change throughout the VIVMP, and in what ways are they motivated to learn mathematics with screencasts? It is notable here that the COVID-19 pandemic began to impact the research study around the eighth week of the VIVMP. As the pandemic impacted the program in several ways, we indirectly investigated how it influenced students’ mathematical knowledge and motivation for learning.

We utilized an Embedded Unit Single Case Study Design in this study to allow for an in-depth analysis of middle-grade students’ mathematical knowledge and motivation for virtual learning (Yin, 2009). Whereas the intervention created a single case for our study, each student participating in the VIVMP became an embedded unit. We studied at a suburban 6–8 grades middle school in central New Jersey. Participants were recruited using the convenience sampling method following approval from the University’s IRB protocol. Thirteen 6–8 grade students (11–14 years old) assented to participate in the 12-week VIVMP and our study. The participants included 12 White individuals, one of whom had special needs, and one Hispanic individual.

The VIVMP was designed only for students who scored between 738 and 755 points (out of 850 total points) on the 2018–2019 standardized mathematics state test; these scores determined that students were either meeting or approaching the state expectations. Recruiting participants from students in this score range was a request of the school of study’s vice principal, as they preferred to have students in lower score ranges participate in an in-person program instead. All students needed to have access to the internet and a computer at home to be able to complete the online program and participate in the study. The first author designed the program to support middle-grade students’ mathematical knowledge. For the selection of mathematical topics covered within the program, the first author reviewed state expectations and standards for each grade level, including the state-provided evidence statements analyzing the school’s performance on the state assessment the year prior. Additionally, mathematics teachers from the middle school where the research took place were surveyed to identify the mathematics topics the students had the highest level of difficulty understanding in their mathematics classes. Using these data sources, a unique twelve-week curriculum was developed for each grade level. The program was designed to be completed by students every week outside regular school day hours at their convenience to maximize weekly participation. All materials for the program were posted on a Google Classroom specific to each grade level at the start of the week with directions for completion. Each week was scheduled as Monday morning through Sunday evening to help students self-pace through the program, but materials were always available once posted.

As screen-casting provides an effective form of technology-based instruction (Sugar et al., 2010), instruction for the VIVMP was provided through weekly asynchronous screencasts, which were created uniquely for each curriculum (all utilizing a direct instruction pedagogy) by the first author using an app for iPad call Doceri (which was retired in August of 2022). The Doceri software had a whiteboard background where slides could be created that the author could write, draw, and insert a coordinate plate. These whiteboard slides were prepared in the app before recording the voiceover, but the solutions and corresponding work to the problems presented were written live during the recorded direct instruction. The screencasts varied in length from 8 minutes to 18 minutes, depending upon the content for that week. The content and questions were pulled from the enVision mathematics 2.0 program for each grade level, as that was the district’s curriculum at the time of the study. However, each direct instruction lesson was unique to the program and was designed in advance by the first author (a certified middle-grade mathematics teacher in New Jersey). The lessons provided direct instruction on the given concept by reviewing key vocabulary words, providing steps to complete the math as needed, and reviewing examples that progressively increased in difficulty. The concepts were tailored to student needs as the weekly lessons made up the curriculum designed using student data from the district of study (prior school year state test evidence statements and a teacher survey soliciting feedback on where the students required more support in the curriculum), as described above.

Students were instructed to check Google Classroom each Monday morning and view the screencast as the first step for the week’s new lesson and received an email when new assignments were posted. They were free to view the screencast at their convenience that week. The goal was that the convenience of the online, independent intervention would help to increase student participation as opposed to a more regimented approach. A corresponding set of multiple-choice, comprehension-based practice questions (between 8 and 12 questions in length) were administered via Google Forms in the same Google Classroom—they posted at the same time the screencast did each week. Auto-grading of the assignments was released to the students immediately upon completing each assignment to provide immediate feedback.

Three forms of data were collected and analyzed from students to answer the research questions: 1) pre- and post-program motivation surveys, 2) weekly program practice assignments, and 3) post-program virtual interviews. The identical pre-and post-surveys, which consist of eight rating-scale items ( Appendix A) examining students’ motivation to complete the program, were adapted from Strickland (2016) and Cho (2012). In the rating scale of the surveys, score options 1–7 represented students’ motivation levels regarding the statement. To measure students’ mathematical knowledge, each weekly practice assignment for each student received a score out of 100. We chose this survey for our study based on the previous psychometric analyses conducted on the survey, showing evidence for its validity and reliability. Finally, semi-structured student interviews were conducted with the completion of the program (Patton, 2015) ( Appendix B).

Our quantitative data analysis included descriptive statistics for the survey items and students’ practice-assignments data. Additionally, we ran a Wilcoxon Signed-Rank Test using SPSS on the survey data to identify any significant change in students’ motivation from the beginning to the end of the study (de Winter & Dodou, 2010; Muijs, 2011). We used a Wilcoxon Signed-Rank Test as a nonparametric alternative to a paired-sample t-test as the data was not normally distributed.

Finally, we analyzed the student interview data using open-coding and grounded theory approaches (Glaser, 2016). The grounded theory approach began with the constant review of each interview transcript, taking interpretive notes regarding what participants phrased and what these meant for our research questions. In this phase of the grounded theory approach, we aimed to identify the essence of meaning(s) (i.e., codes) for each participant regarding their achievement motivation for mathematics and online learning. Secondly, we constantly compared the codes from the transcripts among participants, which allowed us to create our initial code list. Using the related literature (Corpus et al., 2009; Middleton & Spanias, 1999; Spinath & Steinmayr, 2012), we finalized major interview themes and sub-themes to answer our second research question and provided their distributions among the participants. These themes were then used to provide the foundation of our grounded theory, with attention to the new version of SDT (Ryan & Deci, 2020). In this final phase, we reviewed our current themes and structured links to new extrinsic motivation categories (i.e., external regulation, introjection, identification, integration) following Ryan and Deci’s definitions (2020).

As documented in Tables 1–3¹, the participating students completed the VIVMP with an overall average score of 77.57 on the program practice assignments (i.e., 72.01, 84.63, and 76.08 for 6- 8 graders, respectively).

The overall average score for the participating middle-grade students during the weeks covering arithmetic concepts was the highest (i.e., 91.38). Students’ overall average scores for the weeks assessing their mathematical knowledge of algebra- and probability-related concepts were also moderately high (i.e., 80.95 and 79.63, respectively, for algebra and probability). On the other hand, students’ average score for the weeks measuring their mathematical knowledge of geometrical concepts was the lowest (i.e., 64.98). It is worth noting that students were introduced to the grade-level geometry concepts for the first time with the VIVMP but had previous classroom-based learning experiences for the concepts corresponding to the domains of arithmetic and algebra. In other words, the online program provided an opportunity to review arithmetic and algebra concepts while it taught geometry concepts. The goal was to review all concepts, but this was altered due to the school-wide curricular changes stemming from the COVID-19 pandemic-induced school closure.

The Wilcoxon Signed-Rank Test revealed a significant change in students’ motivation after the program compared to its start (Table 4; see  Appendix A for the statement of each Survey Item). The pre-survey was taken during the week of January 22, 2020, before the program began, and the post-survey was taken during the week of May 11, 2020, following the completion of the program.

The post-survey results reflected a statistically significant decrease in students’ interest level in completing the VIVMP compared to their rating in the pre-survey (Z = 2.060, p = 0.039). The significant change in item 1 (interest) indicates that students’ intrinsic motivation for learning mathematics with VIVMP decreased. While there were also some declines in participating students’ motivation to complete the program, considering the mean scores for the other survey items, these changes were not statistically significant. Our findings could be attributed to the COVID-19 pandemic, which began around week 8 of the VIVMP. Students were highly impacted by the rapid change to their learning environment and life, which did not leave a high desire to complete the intervention program in addition to their regular schoolwork (which became virtual). Other studies show the same results, relating the decline in students’ intrinsic motivation and lack of learning effort due to social isolation and loneliness during the pandemic (Berger et al., 2021; Tsai et al., 2023). During the COVID-19 pandemic, the closure of schools resulted in many middle-grades students lacking suitable study environments and missing out on essential social interactions with their peers and teachers; this lack of access impacted young adolescents’ intrinsic motivation considering their unmet developmental social and cognitive needs (Combette et al., 2021). Secondly, students might have lacked the self-directed skills necessary for asynchronous online learning with screencasts, which are hard to practice for middle-grade students compared to secondary school students (Tay et al., 2021).

The interviews were conducted in May 2020 following the completion of the program. As seen in Table 5, the open coding process over the student interview data revealed three major themes and eight sub-themes about participating middle-grade students’ motivation to learn mathematics with screencasts throughout the VIVMP. As we described before, we made connections between our initial themes and extrinsic motivation categories by Ryan and Deci (2020) through a comparative analysis between our data and SDT. More specifically, as students viewed having higher grades and free time as external rewards, we labeled the performance goals and preference for quick work sub-themes as an external regulation category under the theme of extrinsic motivation. On the other hand, we categorized the parental expectations sub-theme as introjection since participant behaviors were regulated by more internal rewards (i.e., praise by parents). Our interview data did not indicate students’ conscious high willingness to do mathematics online (identification) or valuing it as related to their other interests (integration).

All themes were high occurring, with 81% of the participants exhibiting the three major themes. Most of the students (i.e., 12 students, 92%) indicated enjoying mathematics (intrinsically motivated) as the primary motivation and parental expectations (extrinsically motivated [introjection]) were the least frequent reason for motivation (i.e., three students, 23%) for being engaged with the online program and screencasts. An example of a student exhibiting intrinsic motivation comes from Student 3’s interview.

Student 3 expressed being motivated to learn mathematics as he states it is “enjoyable” to learn mathematics because it is “easier” than other subjects for this student. The intrinsic motivation here comes from the enjoyment of learning mathematics, as the subject itself is not difficult for the student to learn. Similar to this, other students’ intrinsic motivation was expressed through their feelings towards mathematics in general—enjoyment and level of difficulty. When students enjoy learning and find autonomy, their intrinsic motivation is higher (Radel et al., 2014).

We also wanted to explore the program’s effectiveness for the students at the end of the interviews and ask their opinions about the VIVMP. One participant stated that his participation in the program “increased [his] confidence and felt [he] was better prepared for the state test.” Each participating student additionally indicated that the program helped them learn mathematics, and they would participate in the same program again. Ten interview participants (91%) gave positive feedback about their learning of mathematics from the screencasts provided with the VIVMP. These students reported that the visual aspects of the screencasts, such as the pictures and seeing the problem being done, and the ability to learn at their own pace (pausing, rewinding, and re-watching) helped them learn and complete practice work. These variables were reported 12 times collectively among the ten students. For example:

This student stated that the screencast helped answer their questions when having difficulty with the material. Finally, nine students (82%) reported that the screencast felt like having a virtual teacher with them due to the visual and audio combination of the instruction, with these variables being mentioned 14 times in total. During the interview, Student 10 stated:

This student emphasized the positive impact having information in a usable format has on learning. Another example comes from the interview with Student 1.

The students reported that screencasts gave them the feeling of having a teacher with them, which indicates that screencasts could help create a meaningful online learning environment, as it is comparable to a traditional environment with a teacher.

The average scores from the practice-assignment data collected throughout the program demonstrated that students in each grade performed moderately well after viewing screencasts, especially when reviewing previously taught mathematical concepts. The lowest average scores in the practice-assignment data were mostly seen for geometry-related concepts (presented during the program’s final weeks). These scores could be explained by a few different variables—one being the under-emphasis on geometry content in middle-grade curricula in the school of study. Yahya et al., (2018) indicated that projecting spatial and 3D concepts and viewing those on 2D platforms (e.g., screencasts) do not allow students to understand geometrical relationships deeply. Accordingly, early integration of geometry in the mathematics middle-grade curriculum with an emphasis on concrete visualizations may be needed to improve students’ overall geometry knowledge in online platforms (Carroll, 1998). It is also possible to interpret this finding due to some students not enjoying the virtual program we designed. Students may have lost their interest in watching the screencasts to help their understanding of content in later weeks of the program, which would align with the decrease in motivation for completing the VIVMP reported in the post-survey data.

Chiu (2022) found that students aged 13–16 in Hong Kong during the 2020 school closures had more success learning online when their basic needs (mirroring the needs from in-person learning) were met. With this, a higher level of engagement with the teacher (i.e., small support groups), autonomy over chosen technological resources, and the use of well-designed materials were noted to increase student motivation within the SDT framework (Chiu, 2022). Accordingly, as virtual curriculum designers, we need to find ways to attract middle-grade students for virtual learning, maintain their engagement with online material, and keep them motivated to learn mathematics independently. Using ideas from SDT, educators need to orchestrate the delivery of the content relevant to the internal values of the students; in this scenario, even if students are not interested in learning mathematics online, they may be engaged with the virtual content by valuing this engagement to achieve their current or future goals (Ryan & Deci, 2020).

Student motivation to learn mathematics with screencasts was also evident within the interview data. Contrary to the student interviews, the only significant decrease between the pre- and post-surveys regarding students’ motivation occurred in their interest in participating in the program. This finding could be due to the added stressor of the pandemic. Çagil and Bulut (2022) found that middle school students in developed countries struggled to adapt to the virtual learning environment because they had a strong foundation for learning in person. In designing asynchronous online mathematics learning environments for middle-grades students, educators need to find ways to increase students’ intrinsic motivation, help them self-regulate their learning, and represent the ties between their interests and learning mathematics online (Tay et al., 2021).

The connection between intrinsic motivation for online learning in the middle school mathematics setting and mathematical knowledge is valuable as it demonstrates that this demographic of students can learn online when properly motivated. This finding is consistent with research stating that intrinsic motivation is the most important motivation for learning in the K–12 setting (Taylor et al., 2014). In another study, Chiang and Lin (2014) reported that students who applied learning-based goals (i.e., having intrinsic motivation) over achievement-based goals (i.e., having extrinsic motivation) found greater success in mathematics as determined by their grades in mathematics class. We recommend that future research should aim to build upon this finding with a larger and more diverse sample size to increase the understanding of what aspects of intrinsic motivation are critical for online middle-grade mathematics learning.

According to Deci and Ryan’s SDT (1985), intrinsic motivation is foundational to learning. Understanding the intrinsic motivation for online learning is critical now, as the COVID-19 pandemic left educators and communities questioning how to educate students under the social distancing guidelines and with caution to safety concerns from educators and families. However, it is difficult to assess the degree to which intrinsic motivation specifically impacts mathematics knowledge in this study as initially intended. While the open coding process revealed that ten students (91%) were intrinsically motivated towards mathematics (e.g., stating that they enjoyed learning mathematics or felt that mathematics is easy), when asked what their greatest motivating factor was, seven students (64%; in comparison to 4, 36%) stated standardized test performance (an extrinsic motivation category). Based on this latter finding, the students’ motivation for completing the program was more extrinsic than intrinsic for most participants. With the new conceptualization of SDT, we may need to view students’ extrinsic motivation to do mathematics online as a step towards being intrinsically motivated. Ryan and Deci (2020) consider that students could internalize an extrinsic motivator (a perceived reward for the action) if they can see the value in their actions to achieve their goals and could associate these activities with their existing interests. In this respect, educators need to consider what interests and goals middle-grade students already have and shape the online mathematics learning opportunities according to this student information.

In the school of study, standardized test preparation occurs each spring, and teachers discuss the state test all year with students during class to help emphasize the heavily tested content. With this, the stress teachers feel to push students to meet or exceed expectations on the assessment is, in turn, pushed onto students. The existence of standardized tests creates a negative cycle, seemingly perpetuating students’ extrinsic motivation reported in this study. Overall, our findings underline the importance of students’ motivation to learn mathematics through screencasts. Future research needs to investigate further the differences between intrinsic and extrinsic motivation for virtual learning in middle-grades mathematics.

Student interview data also underlined the advantages of asynchronous learning middle-grades mathematics through screencasts; students perceived their mathematics learning was enhanced with technological and visual affordances, the presence of a virtual teacher, and the ability to review previously learned mathematical concepts. Learning from screencasts afforded students to perceive a digital autonomy of mathematical support online (Chiu, 2021). Some aspects of the VIVMP provided opportunities for students to experience such digital autonomy and support: students heard the voice of their mathematics teacher in the screencasts, viewed the solutions to mathematics problems they recently learned in their mathematics lessons, and engaged in related practice assignments after the screencasts. The VIVMP might improve its quality with attention to teaching and learning mathematics through inquiry, more asynchronous interactions between students and the teacher, and availability of systematic and meaningful feedback and scaffolding (Cevikbas & Kaiser, 2020; Kalogeropoulos et al., 2021). For this intervention program, the screencasts could have promoted inquiry by posing more questions and instructing the students to pause the videos while working on their solutions to those questions. With most of the content being “review material,” it would be appropriate for the students to have the challenge of independently exploring the content before having the screencast provide the needed reinforcement of direct instruction and solution checking. Additionally, screencasts could be used as an intervention in the classroom for students to re-learn old skills or be challenged by new skills, independently, while a live teacher is present to field questions as needed, as seen with programs such as IXL and iReady.

There were several limitations to the study that surfaced in response to the COVID-19 pandemic. The most prominent limitation was the school closure in March 2020. The VIVMP began in January 2020. Many students who were previously active in their weekly assignments disengaged from the program after the school closure, which could be a response to the sudden and shocking changes in their lives due to the pandemic and the challenges of completing school entirely remotely. The school district of the study did not implement consistent live sessions for virtual learning until the Fall of 2020. Along with the decline in participation, the school closure also made recruiting participants for the study more difficult. Families were stressed in the spring of 2020 during study recruitment and were disengaged from the school. Along with this, many program participants were unwilling to participate as they had stopped completing the VIVMP when the school buildings were physically closed. The COVID-19 pandemic also impacted data collection and analysis. The state of New Jersey canceled state testing—the New Jersey Student Learning Assessment (NJSLA)—during the study year 2020 (NJ DOE, 2020) and the following year 2021 (NJ DOE, 2021). With this, the scope of the study had to be adjusted to report on student performance regarding mathematical knowledge during the program rather than their mathematics achievement on the NJSLA.

Additionally, due to the lack of NJSLA testing and the smaller sample size, no statistical analysis could be conducted to determine if there was a statistically significant correlation between student mathematics achievement and student motivation. Therefore, a delimitation is that the researcher chose to remove this from the analysis due to the circumstances. The post-program motivation survey was completed after the 12^th week when student disengagement was high due to the pandemic. The pandemic-induced disengagement could have been variable in having fewer responses than the pre-survey for the post-survey. We also know that other surveys could have been used to measure students’ motivation to learn mathematics online. In the survey we used, the way some of the statements presented might have confused some participants. For example, Sergis et al., (2018) used a different survey to examine the impact of FCM on K–12 students’ learning experiences, adopting SDT as their theoretical framework. A future study that investigates the motivation of students while learning mathematics through screencasts may utilize a survey similar to the one developed by Sergis et al.

The student interviews were still able to occur, but another limitation was that they needed to occur over the Google Meet platform instead of face-to-face. Scheduling the interviews was difficult, and students often needed reminders and phone calls home from their parents and guardians to log in at their scheduled time. The students were quarantined in their homes for the interviews. At this beginning stage of the virtual student-teacher interaction, students were often nervous about meeting online.

As educators, we must meet our students’ various needs and prepare them to be successful in the forthcoming stages of their education. The data shows that middle school mathematics students need more support to learn mathematical content successfully. Voluntary virtual learning middle grades mathematics programs, utilizing screencasts as an instructional modality, show promise to help students increase their mathematical knowledge. Such programs could help increase their overall mathematics achievement in the future.

Reinforcement of knowledge was demonstrated to have a higher impact on student success than the introduction of knowledge through screencasts. However, the achievement split between algebra and geometry-based concepts was prominent in this study, and more research is needed to determine if middle-grades students benefit most from screencasts as a review or if geometrical concepts need to be presented with a more substantial 3D technological presence. Based on the current study, virtual learning for middle-grades mathematics can be effective when implemented in a manner that mimics classroom-based learning; this was similarly found by Chiu (2022), who stated that online learning needs to meet the exact needs students experience with traditional in-person learning.

Students’ intrinsic motivation for learning is considered imperative to student success. Nevertheless, the population in this study seemed to be most self-aware of their extrinsic motivators for learning mathematics. Regarding this, mathematics educators should strive to instill the love of learning mathematics and its value into their students. Students may need lessons on the importance of learning mathematics to help them understand why their learning is critical to their success, not their grades. Virtual learning has been changing our K–12 education systems more rapidly than ever before following the COVID-19 pandemic. Due to the connection established between virtual learning and motivation, middle-grades mathematics teachers need to help students spark their intrinsic interests and build personal value to learn mathematics. This goal can be achieved by presenting the importance of studying mathematics for personal growth (value) and enjoyment (interest) rather than the current focus on extrinsic variables, such as grades and testing. Considering the different motivation categories described by Ryan and Deci (2020) and building on our conclusion, future research is needed to compare and contrast the effects of different virtual learning programs on meeting the needs of students motivated to learn mathematics differently.

1. How motivated were you to complete the program? Did that change at all over the course of the program?

2. What was the greatest source of motivation for you to complete the program?

3. Did you find the program helpful? Why or why not?

4. How long did it take on average for you to complete the program each week and was it difficult for you to find the time?

• 5. What did you think of the screencasts as a form of online instruction?

• 6. How do you think screencasts helped you to learn mathematics? How do you think screencasts motivated you to study mathematics more?

• 7. In what ways do you think screencasts motivated you to learn more about math?

• 8. Would you say you enjoy learning mathematics?

• 9. Is it possible to get a poor grade on a mathematics homework or test and still be pleased with what you learned? Explain.

• 10. I know a middle school where there were no grades given in math. Suppose we had such a system here. How do you think you would react to that in a math class? How would it affect what you would do in your math class?

• 11. Did this program help you? If so, how?

• 12. Would you participate again? Why or why not?

• 13. Would you recommend this program to other students? Why or why not?

• 14. Are there any recommendations you have for this program in the future?

Participating students completed an average of nine questions in each week’s practice-assignment. Each student’s score for each practice-assignment was calculated between 0–100, where 100 represented full mathematical knowledge.