Warning: This is a VERY long post. I apologize for all the detail, but – then again – I won’t apologize for providing clarity!
I have always been irked by certain student behaviors: coming to class late, not handing in work on time, and asking to use the restroom while we are in the middle of learning. Recently I began to see a connection between these behaviors. So, I did some research, looked at my data, and created an experiment to see if I could make a difference in these areas.
Begin With Data
I gathered together student work submission data, classroom attendance data, and student office-referral stats. Right away, I noticed that there was a core group of students who appeared in each list. Then, out of curiosity, I compared this group to our middle school standardized testing scores. When I looked at the reading scores of my students, I immediately noticed that same core group: the students who were late submitting work, were regular behavior issues, and had higher than average tardies, were also among the lowest scores in our reading assessment.
The next step in my data-collection process was not that intuitive. I decided to look at the students who regularly ask to go to the restroom in my class. Part of the reason why I decided to look at this data was simply because I had the data available. To ensure students are not abusing this privilege, and as a method of ensuring I always know where students are at a given time, many years ago I instituted an exit sign-out system in my classroom. Students, when they wish to use the restroom, must write their name, the date, the time they left the room, and the time they returned to the room. In addition, this data grew in terms of interest to me because – as a result of data collection above – I began to notice a pattern among the students who seemed to go to the bathroom most frequently during class time. So, I examined my sign-out sheets and discovered that my suspicions were well-founded.
|Students Appearing At Least Three Times in Above Late Work Data||Students With Late Work Who Used the Restroom 10 or More Times During the Current School Year|
This restroom data was of particular interest to me as I was able, thanks to the dates noted on the exit form, to determine what activities were being conducted in class during the days with the highest frequency of restroom visits. The days where students were working on individual, teacher-centered, less-engaging activities (such as note-taking skills and self-directed research skills) significantly more students used the restroom than on days when students were working on partner-based, more interactive, engaging, and creative activities. During one four-day stretch of self-directed and intensive research in February, for instance, 34 students used the restroom. During one four-day stretch of work on a more engaging and interactive activity in early March, only 9 students used the restroom.
Could it be that students were engaging in various misbehaviors and avoidance strategies because they struggled to access classroom content? Were they avoiding the work because they couldn’t do the work? Or, students did not want to submit work for assessment until they had an opportunity to ensure they understood the expectations, and until they have had time to have their work reviewed by a sibling, friend, parent, or tutor.
What the Research Says About Avoidance
An exploration of student avoidance strategies, and how to best address them, begins with a look at avoidance-related research. One study I looked at found a link between avoidance strategies and student self-worth. In 2013, Dr. Aysel Esen Coban of Hacettepe University conducted a study focused on strategies employed by adolescents, including problem solving, seeking support, self-blame, and avoidance The study endeavored to determine which ones resulted in a successful reduction of stress (Coban, 2013). In the study, almost 400 adolescents were surveyed in terms of their sense of wellbeing and the “Stress Coping Strategies with Stressful Experiences” they employed in stressful situations (Coban, 2013). The study found that the strategies of problem solving and seeking social support resulted in higher senses of self worth among the participants, while avoidance resulted in a lower sense of self worth. Coban concluded that adolescents should be taught these more-effective stress coping strategies.
Another study found a similar connection between avoidance and student self-esteem. Bernhard Mullner and Martin Scheuch, of the University of Vienna, explored the struggles of second-language-learner students when they experience “linguistic overload” (Müllner and Scheuch, 2017). In order to successfully produce “new knowledge” in a Biology class, students were required to apply academic language that was different from the social language employed throughout the day (Müllner and Scheuch, 2017). To determine how second-language-learners coped when they encountered this “linguistic overload” the researchers conducted a case study of a particular student. The student was placed in a class where the academic language required to be successful was beyond their ability and then observed the student while they worked on a number of activities. The subject employed avoidance strategies when the language demands became too challenging. Follow-up interviews revealed that these strategies were employed to maintain positive self-image in a situation where they were unable to be academically successful. In situations where language support and scaffolding was provided to the student, avoidance strategies were not employed (Müllner and Scheuch, 2017).
Precisely what component of self-esteem is being protected by avoidance strategies? Are students interested in protecting their social image, or are they interested in their academic achievement? Stefanie Obergriesser and Heidrun Stoeger, of the University of Regensburg, conducted a study entitled The Role Of Emotions, Motivation, And Learning Behavior In Underachievement And Results Of An Intervention (2015). In the study, the researchers endeavored to determine which concept was a more powerful predictor of underachievement among elementary students: their self-concept, or their sense of self-efficacy. Self-concept was defined as “the general perception about themselves” while self-efficacy was defined as “an individual’s judgement about being capable of successful performance in given academic tasks” (Obergriesser and Stoeger, 2015). The study looked at 24 students who were identified as underachievers in terms of a disconnect between their grade-point average and their IQ score. The results indicated that the less self-efficacy (and the more anxiety) reported by subjects, the more likely they were to be underachievers academically (Obergriesser and Stoeger, 2015).
The next step is to determine how avoidance strategies can best be addressed by educators. Xiu Yu, of Qinqdao University, observed second language learner student behaviors during a number of writing activities. The study discovered that when faced with difficulties in terms of writing in a second language, students employed avoidance strategies in order to avoid making mistakes (2017). This use of avoidance will result in a lack of success in terms of the accumulation of new knowledge and, as such, educators need to focus on increasing “the quality and the number of target language input” as well as helping students build their confidence, build their self esteem, and reduce anxiety concerning future success (Xiu, 2017).
Another study determined, more precisely, the psychological areas educators can target to reduce avoidance strategies. Fernando Betoret and Amparo Artiga, of the University of Valencia, conducted a study of the relationship between the sense of satisfaction in terms of the basic needs of students and the employment of avoidance strategies (2011). The basic needs identified in the study included autonomy, competence, relatedness, and belonging. Autonomy was defined as the belief that people feel they are the “cause of their behavior”, competence was defined as a sense of effectiveness in terms of one’s behavior, and relatedness was defined as feeling connected to, and understood by, others (Betoret and Artiga, 2011). The study was based upon questionnaires completed by 157 students concerning the above relationships. The results of the survey indicated that when students had satisfied their basic needs, in the areas of autonomy, competence, relatedness, and belonging, there was a decrease in the employment of avoidance strategies and students felt able to “achieve optimal academic performance” (Betoret and Artiga, 2011). Conversely, when the above needs were reported as not being satisfied, there was a reported increase in the employment of avoidance strategies and, as a result, an attempt to “protect their public image of competence” (Betoret and Artiga, 2011). The authors concluded that teaching strategies should consider students’ psychological needs as well as their academic needs.
The use of avoidance strategies by students is more complicated than simply avoiding effort. Students are employing avoidance because they feel unprepared to complete a task, and they are anxious to protect their sense of being capable individuals. As such, arming students with the tools necessary to feel successful, as well as providing them with opportunities to demonstrate success, should result in a decrease in avoidance strategies.
Plan of Action
Based on my data and the above research, I developed a hypothesis that some of my students were engaging in work avoidance because they felt insecure in their ability to effectively complete my assignments. So, if I could somehow boost student confidence in their abilities, then I should see a reduction in avoidance behaviors. To test this theory, I created a graphic organizer tool that – if explained, modeled and used effectively – should result in better writing and, therefore, higher student confidence in their writing. The use of this tool (and the modeling of it) was a significant change in the existing writing process for this population. Students have been taught how to write a paragraph in previous grades. As such, many teachers assumed all students are capable and confident in their writing and require little in terms of support in constructing a paragraph.
A number of colleagues were consulted throughout the research process to provide additional support and information. They helped in the development of the graphic organizer tool to be employed, and the native Spanish-speakers provided additional insight into the struggles that ELL students encounter when working in another language. Once data was collected, this team was regrouped to help analyze the information and discuss patterns or observations related to the findings.
The data for this research was collected in two ways. First, baseline data was gathered to determine the extent of the use of avoidance strategies by the student subjects prior to the experiment. This baseline data was collected via existing restroom exit sign-out data, classroom attendance statistics, and assignment submission data. Next, Field Notes were employed to record observations throughout the experimental process with a focus on student avoidance behaviors (tracking differences between the group utilizing the change in strategy and the control group not utilizing the change).
The above data collection tools were selected because both were ones that had been employed regularly and were familiar to me, and – therefore – could be used quickly and easily. Furthermore, although the presence of an observer can change behavior, observation data, such as Field Notes, has an accuracy advantage in that it tracks student behaviors directly, not student opinions of what was occurring (Mertler, 2017).
The baseline data concerning student avoidance strategies had been pulled from existing data collected throughout the school year, but not for use in this experiment (Mertler, 2017). For instance, restroom usage data was gathered through a student exit sign-out form positioned next to the classroom door. Students were required to complete the form whenever they exited the classroom to use the restroom. Student attendance data was gathered through the daily classroom attendance tracking records. And, student work submission data was recorded through my existing assessment and tracking methods. During the experimentation process, data concerning student behavior was gathered through observation and tracking.
The data collected was formative in nature, gathered via observation and tracking throughout the instructional process for the purpose of informing and shaping instruction (Mertler, 2017). Summative data was not required as the focus was not on a snapshot of achievement, but rather in day-to-day student behavioral changes.
Prior to the start of experimentation, collaboration with colleagues occurred via the Critical Friends Group model of data collection. For this particular experiment, the collaboration provided little in terms of valuable feedback concerning the experimental question, the experimental process, or the analysis of the results. For instance, colleagues were curious about a possible connection between student confidence and the use of avoidance strategies. However, ultimately, the colleagues participating in the process clung to existing beliefs about the students. When looking at restroom and tardiness data and data from the school’s standardized reading test scores, one colleague remarked: “Yes, but look at the amount of time some of these student spent on their reading tests – they were just clicking buttons to get the test over with. You can’t trust those results.” One area where a number of colleagues did provide value was in the area of student second language. A number of colleagues, like many of the students highlighted through the baseline data, are local, native Spanish speakers. These particular colleagues provided insight in terms of the struggles of native Spanish-speaking students with academic language acquisition and usage. The experiment was adjusted such that students were provided with instructions for understanding and using the graphic organizer tool that supported the learning needs of second-language users. For instance, when demonstrating the use of the writing tool, important/new vocabulary was explained and, when it appeared on the board, was written in a colored font to ensure it was highlighted. In addition, complicated steps in the process were scaffolded with an illustration to help students better understand the steps. Students were also paired with a Spanish-speaking partner during the explanation process so the pairs could discuss, in their own language, any new concepts or steps they were confused about.
Student avoidance behaviors prior to experimentation were established as a baseline through existing data sources, including restroom sign-out forms, school attendance records, and work submission tracking forms. Following the experiment, student behavior was review utilizing the same existing data sources in order to identify any behavioral changes. Looking at a quantitative change in more than one avoidance strategy (restroom usage, tardiness, and late work submission), rather than simply one source, provided an opportunity to confirm a change in student behavior. Furthermore, tracking data through the use of Field Notes – teacher observation notes gathered while students were working with the new graphic organizer tool – provided additional confirmation and validity.
The student behavior data indicated that the use of the graphic organizer tool had a significant impact on the submission of student work. Among the treatment group of students, 74 percent turned their writing work in by the posted deadline. In the control group of students, 41 percent turned their work in on time. In terms of student restroom use, restroom use for the treatment group dropped in number from the day immediately prior to the beginning of the experiment and the day of the experiment. On the day prior to using the graphic organizing tool, students were front loaded with information about the topic in which they would be writing. This class period involved student reading, class discussions, and some teacher-led lecture. During this day, 17 students (out of a total of 49) in the treatment group visited the restroom. In the control group, during this front loading day, five students (out of 34) visited the restroom. In terms of percentages (as these two groups are of different sizes), these numbers translate into 40 percent and 15 percent respectively. During the experimentation process, restroom usage for both groups was five students. This represented a reduction in restroom usage for the treatment group of 29 percent and no change for the control group. In terms of student attendance, the results were inconclusive. For the front loading day, prior to experimentation, there were seven student tardy in the treatment group and zero students tardy for the control group. For the experimentation day, both the treatment and control groups had one student tardy. For the treatment group, this represents a decrease in tardies of 12 percent. For the control group, tardies increased two percent.
The field notes collected during the experimentation process provided interesting data. While moving among students, observing behavior and providing normal teacher support, students in provided a number of interesting (and unsolicited) comments. One student in the treatment group said, while discussing the graphic organizer tool, “Doing this is so much easier. I’m going to use it from now on.” One student in the control group, while working on the writing assignment without a scaffold tool, said “I feel lost.” Another student in this latter group said “I don’t feel organized. This is messy.”
The data provided some clarity concerning the research question. But, the results were incomplete. In terms of student behavior and academic confidence, the above student feedback indicated that there is a connection between the graphic organizer tool and student confidence in their writing. The behavior tracking data indicated that the avoidance behaviors decreased in the group employing the graphic organizer. However, the data alone did not provide a complete understanding about student behaviors. This experiment, for instance, occurred during the academic cycle in which the school had scheduled parent conferences. During this cycle, report cards for the third quarter of the school year were also released to parents. In this situation, student behaviors may not have been normal. Students were made aware of information that may have impacted their behavior, such as their grades and the number of tardies they possessed for the school year. In general, the data collected provided much information about the quantitative change in student behaviors, but it did not provide information about why student behavior was changing. This why information could have been gained via student survey data. In the treatment group, there were two students who did not complete either the graphic organizer tool or the accompanying writing assignment. Both individuals were caught using their technology inappropriately (one was watching a video, the other was playing a game). The data does not reveal what happened in this situation. A one-on-one interview would have been informative. And, the quantitative data collected did not consider other circumstances, such as the time of day. Each of the student class blocks were scheduled at different times over the two-day experimentation process. Some students were in the first block of the day, others were in the second of two back-to-back classes with no break in between, while still others were working in the final block of the day, right after lunch. The data collected would not be able to measure the impact of these schedule-related variables.
In terms of teacher practice and student learning, the data revealed that some students are not open about their academic ability. Rather than discovering a deficiency and then (with assistance) developing a strategy to address it, some students prefer to mask the deficiency behind behaviors. Educators need to be aware of this phenomenon so that they can discover the reality behind particular behaviors (and grades) and then develop the strategies necessary to precisely address them. This will require educators to develop a deeper understanding of their students and to dig for understanding, rather than resting on assumptions.
In terms of the literature review, the action research project clarified the connection between student avoidance behaviors and student confidence. To avoid the risk of being exposed, the research indicated, many students mask their lack of confidence with a lack of performance (Obergriesser and Stoeger, 2015). The analysis conducted reflected the findings in that when student confidence was boosted, through the use of a scaffolding tool, the number of avoidance behaviors usually employed was reduced in number. The results indicate that educators should spend time addressing issues of student confidence before reacting to student behaviors.
Implications for Practice
The findings of my research project provided confirmation about a connection between student behavior and student self esteem. However, after reflection about the overall research process, the data gathered did not necessarily provide complete details about this connection. Future versions of this project would benefit from the inclusion of a student survey, administered both before and after the process, to fully determine the impact of the scaffold tool used in the experimentation process. In addition, the findings – upon reflection – may have been affected by scheduling issues. Moving forward, the following changes would be made in a future version of the project:
- A student survey should be created for establishing baseline data concerning student self-esteem and academic confidence.
- Prior to the revised research process, the school calendar should be examined to ensure the subsequent experimentation does not coincide with high-stress school events or activities. In addition, a meeting should be organized with colleagues to discuss the scheduling of high-stakes assessment activities to ensure experimentation does not coincide with them. Finally, prior to the research project, an experimentation schedule should be created to ensure that the treatment and control group activities occur at consistent times of day and do not conflict with back-to-back classes or the end of the school day.
Kevin Barry, an elementary teacher interviewed in the Laureate Education video, Pick-a-Researcher, Week 1—Introduction, talks about how his research projects were based on topics that he regularly discussed with colleagues or felt a good deal of passion about (2015c). In my day-to-day practice, there are a number of areas of concerns that trigger a desire for change. This experience has provided me with a systematic process for exploring these areas and developing strategies to address them. Furthermore, this experience underscored the importance of data in a continuous-improvement model. To precisely determine concerns, teachers need to acquire and analyze the right student information. Then, strategies are developed to address the concerns. But, it is necessary for educators to gather new data to measure the effectiveness of the strategies implemented, reflect on the process followed, and – if necessary – make revisions to the strategies or the process of implementation employed.
The results of this research project revealed that student behaviors are not necessarily arbitrary or a result of a lack of effort or interest, on the part of the student, in learning. With this in mind, teachers could make a positive difference in the learning of their students, and in the lives of their students, by spending time helping students develop their skills. As a result, the confidence in their skills could translate into an improvement of their overall self concept (Obergriesser and Stoeger, 2015).
It is exciting to consider just how profound and far-reaching this focus on student confidence could be. There could be, as this particular research project was focused on, an immediate impact on student attendance and on student work submission. However, other student behaviors could be impacted, including disruptive behaviors and masking their areas of academic need. These changes would allow educators to focus more on instruction, rather than on discipline, and would help teachers target and address particular student needs.
Whew! That was a LOT. I hope this encourages you to look at your data and try some changes in your instructional practices.
Betoret, F. D., and Artiga, A. G. (2011). The Relationship among Student Basic Need
Satisfaction, Approaches to Learning, Reporting of Avoidance Strategies and Achievement. Electronic Journal of Research in Educational Psychology, 9(2), 463–496. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=eric&AN=EJ946110&site=ehost-live
Coban, A. E. (2013). Interpersonal Cognitive Distortions and Stress Coping Strategies of Late
Adolescents. Eurasian Journal of Educational Research, (51), 65–83. Retrieved fromhttp://search.ebscohost.com/login.aspxdirect=true&db=eric&AN=EJ1059819&site=ehost-live
Goldstone, L. (2003). The mother tongue: The role of parent-teacher communication in helping students meet new standards. In E. Meyers & F. Rust (Eds.), Taking action with teacher research (pp. 63–78). Portsmouth, NH: Heinemann.
Laureate Education (Producer). (2015c). Pick-a-researcher, Week 1—introduction [Video file]. Baltimore, MD: Author.
Mandinach, E. B., and Gummer, E. S. (2016). Data literacy for educators: Making it count in teacher preparation and practice. New York, NY: Teachers College Press.
Mertler, C. A. (2017). Action research: Improving schools and empowering educators (5th ed.). Thousand Oaks, CA: Sage.
Müllner, B., and Scheuch, M. (2017). Avoidance Strategies as a Result of Linguistic Overload in Biology Class. Orbis Scholae, 11(3), 29–46. https://doi.org/10.14712/23363177.2018.274
Nguyen, Q. T. (2007). Understanding high school black male students’ achievement and school experience. In C. Caro-Bruce, R. Flessner, M. Klehr, & K. Zeichner (Eds.), Creating equitable classrooms through action research (pp. 100–124). Thousand Oaks, CA: Corwin Press.
Obergriesser, S., and Stoeger, H. (2015). The role of emotions, motivation, and learning behavior in underachievement and results of an intervention. High Ability Studies, 26(1), 167–190. Retrieved from https://doi.org/10.1080/13598139.2015.1043003
Tadayyon, M., Zarrinabadi, N., and Ketabi, S. (2016). Teachers Avoiding Learners’ Avoidance: Is It Possible? Clearing House: A Journal of Educational Strategies, Issues and Ideas, 89(1), 1–6. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&db=eric&AN=EJ1094021&site=ehost-live
Xiu Yu. (2017). On the Avoidance Phenomenon in Writing. Journal of Language Teaching & Research, 8(5), 948–952. Retrieved from https://doi.org/10.17507/jltr.0805.15