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The Effects of Different Expectations on a Student’s Motivation and Thinking Ability During a Test Ramya Kumar and Tooba Alwani 1 Science Department, Great Neck South High School, Great Neck, NY 11020, U.S.A. § Both authors contributed equally to this work Character count: 41,613 Running Title: The Great Expectation 1

The Effects of Different Expectations From Teachers on Students

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The Effects of Different Expectations on a Students Motivation and Thinking Ability During a TestRamya Kumar1 and Tooba Alwani1

1Science Department, Great Neck South High School, Great Neck, NY 11020, U.S.A. Both authors contributed equally to this workCharacter count: 41,613Running Title: The Great Expectation

AbstractThe education of our students, especially in this day and age, is very important to the world. We are constantly looking for new ways to increase the amount of knowledge that we possess. Previous studies have shown that different expectations of how students will be assessed on information can lead to better qualitative and quantitative learning performances. Additionally, if one is expected to teach, his or her mind prepares and studies the information differently from those who expected to take a test; however, the results of these studies have produced unclear conclusions. Our studys purpose is to look further into their analysis with a more complex measure of learning. This different approach, based on Bloom's revised taxonomy, may produce stronger insights regarding students learning and thinking ability. To do this, we split the students into different conditions and had the students read a paper that they later received a test on. Depending on the condition, some expected to teach the information and others expected to take a test. However, both groups were assessed with a Bloom's taxonomy styled test. The scores were compared between the conditions. It was found that the expecting to teach group did better on the short-answer questions and were more involved in their preparation. The results of this study could eventually impact learning and teaching in our education system.

Keywords: Deeper learning / Expectations / Blooms Taxonomy / Teaching

IntroductionPeople live in a world that is constantly changing- quicker than ever before! With the technological advancements, more new careers that demand higher level thinking - are opening up to our future generations. Despite our world advancing rapidly, Americas education system is failing to catch up. According to the Programme for International Student Assessment (2009), the United States used to rank 1st in education. Now, other countries are more efficient in preparing their students for the future that lies ahead. This is partly due to the lack of deeper learning initiated in our education system; students just memorize tons of information for a test without applying or understanding it. According to Hewlett Foundation, students who are engaged in deeper learning are more motivated to be involved in education-based careers, promoting higher learning performances. Deeper learning also involves students to not only gain knowledge and recall facts but also apply what theyve learned to real life situations. These are a few of the skills employers are looking for in these new careers the key to a students success. Because of this, maximizing a students learning performance and encouraging deeper learning has always been of great importance to the world. We are always looking for new ways of improving students learning ability to help them succeed in the future. Deeper learning is not only beneficial towards our success, but it also pivotal towards our well-being. According to a Roscoe & Chi (2007), 7 in 10 people think that learning can lead to a better quality of life. Additionally, Wilson et al., (2007) found that deeper learning improves memory and cognitive abilities in a lifelong sense. With all the benefits of deeper learning, it is important that educators encourage and incorporate it within our education systems. In order to incorporate deeper learning in our education systems, researchers must first understand what can effectively maximize students learning performance. Active learning has shown to improve students learning, thinking, writing, and attitude (Prince, 2004). Students tend to better understand the material and information when the activities are hands-on and engaging (Prince, 2003). Students can become active learners by engaging in activities that make them responsible for their learning. A study done by Ruhl et al. (1987) illustrated this by having students to take notes to a lecture. Once the lecture was over, the students were asked to clarify and discuss their notes with a nearby partner. The researchers found that this activity helped students recall more of the information on a short-term recall test. The researchers concluded that discussing the information with other caused the students to think more; therefore, producing higher learning performances. Along with thinking more, engaging actives can make students remember the experience easily and cause them to reflect back on it, this is essential for students to understand the material (Hmelo-Silver, 2004). One of the many way to get students involved in active learning is by having them teach material. Research shows that the teaching process can beneficially impact students learning performance because it involves hands-on practices and reflective knowledge building - students use their understanding of the information and prior knowledge to explain information to others better (Fiorella & Mayer, 2013). Teaching also involves different metal activities - such as the following: summarizing ideas, identifying vital concepts, making connections to outside sources, and organizing material - that can help make the information more understandable to an audience (McKeachie, Pintrich, Lin, & Smith, 1986). This mental activity is known to show beneficial results in learning new information. Additionally, students who teach the new information to another student show that they are more motivated to learn about that topic. This encourages and motivates them to learn even more about the information (Benwet & Deci, 1984). Another benefit of teaching is that it promotes a learning approach that it forces one to focuses on the main concepts and big pictures while using factual details to support it. Because teaching involves a communication aspect, many researchers have found that it efficiently improves students preparing for futures in educational careers (Cate & During, 2007). Peer teaching and teaching has been an effective method towards getting student involved in deeper learning; however, it can be a time consuming process even can be a distraction to some - to incorporate into everyday education. While teaching is beneficial towards the learning process, many researchers have looked into the expectation to teach to be as impactful as actually teaching. Previous studies have shown that different expectations could lead to better qualitative and quantitative learning performances. For example, Szpunar, McDermott, and Roedigner (2007) study showed that the expectation to take a cumulative test caused students to do better on free recall and organization tests than those who just expected a normal test. Additionally, Lundeberg & Foxs (1991) study found that those expecting a free recall test did better in recall and recognition tests than those just expecting a recognition test. If one is expected to teach, his or her mind prepares and studies the information differently than those who expected a test. This difference in mindset may produce more efficient in learning and understanding the information. This conclusion is based on research that shows that learning by teaching involves very different cognitive processes as compared to learning with the expectation of a test. Expecting to teach information can cause students to force on the main concepts and also increase their retention of factual knowledge (Nestojko, Bui, Kornell, & Bjork, 2014). This cognitive process causes those expecting to teach to devote more time revising and condensing to the most important information for someone else to understand (Fiorella & Mayer, 2013).Despite the benefits of expecting to teach, the results of most these studies have produced unclear and conflicting conclusions regarding if expecting to teach is actually beneficial. Some studies have found positive outcomes. A study done by Bargh and Schul (1980) gave participants material to study for and were either expected to teach it to someone else or expected to answer questions on the topic. The researchers found that those expecting to teach did better on retention tests as compared to the other condition. Another study done by Benware and Deci (1984) had a similar set up to Bargh and Schul, and they found that students expecting to teach did better conceptual learning on a certain topic than those expecting a test. Another study done by Fiorella & Mayer (2013) found that the expecting to teach group did better in both memory and conceptual learning. The study supported this showing that subjects the who expected to teach did equally well on memorization questions as compared to the expecting to take a test group ,but they did better on conceptual questions. Some studies have found both negative and positive outcomes from expecting to teach. In Nestojko, Bui, Kornell, & Bjork (2014) study, their first experiment shows that the expecting to teach group did not outperform the expecting to take a test group in conceptual questions; however, their second experiment found that they did. Some studies support these negative results, saying that teaching induces stress, so it becomes useless to the learning process (Rohrbrek et al., 2003). While the expectation to teach can have beneficial results, because of these inconclusive results produced so far, researchers need to validate these findings with more precision than before. These conflicting results may be partly due to the dependent variables used to measure learning. For example, many of the studies mentioned before involved free recall tests to measure how much a student remembers material (Nestojko, Bui, Kornell, & Bjork, 2014). This measure focuses mainly on memory and retention and fails to consider deeper learning processes such as applying the information. These studies may find more conclusive results regarding the impact of teaching if they enhanced the definition of learning. This studys purpose is to look further into the previous studies analysis with a more complex measure of learning. The measurement used is based off of the Revised Blooms taxonomy model. Blooms taxonomy is composed of educational objectives placed in a certain order to represent different levels of thinking (Bloom, 1956). It has been revised by Anderson, Lorin W. & Krathwohl, David R. (2001) to clarify any confusion from since it was first created. It starts with the lowest level: remembering. Remembering is when one is able to recall the information from memory. The order then moves up to understanding: which is one is able to explain concepts. It then continues to applying: one is able to take the information and use it in another similar situation. The next level is analyzing: when one is able to group the information into categories and understand relationships among them. It then moves up to evaluating: which is when one is able to justify the reason why something happened. And finally, the order reaches the top level: creating. This is defined as the ability make new ideas and view a new perceptive with the information (Aiken & Lewis 1982). Blooms taxonomy helps categorize the different thinking levels in short answer or multi-choice questions. This allows for deeper learning to be assessed on tests. It is hypothesized that those expecting to teach will not only do better overall on the test but also in questions that deal with higher levels of thinking (such as evaluating and creating) as compared to those expecting to take a test. It is also hypothesized that due to the mentioned benefits of teaching, students will be more motivated and engaged in the learning process (mindset (Benwet & Deci, 1984).

MethodsParticipants Data was collected from three of Ms. Sorises AP psychology classes. There was a total of 67 participants, all of whom had to sign a consent form to participate and get credit for this study. Each class period was assigned a different condition; their sample sizes are the following: 24 students for the expecting to teach condition, 26 for the expecting to take a test condition, and 17 for the no expectation condition. The classes represent the general population no one was selected based off of race, gender, ethnicity or social status. However, only 11th and 12th graders were in AP psychology. All participants were given participation credit, as well as an incentive to earn raffle tickets to win a gift card. MaterialsAll classes were given material to read in class. The material given was an article in the topic of developmental psychology a topic that the students havent studied yet. The article was about a study conducted by Gbison & Walk (1960) in which they created an apparatus (known as the visual cliff) to determine if depth perception was innate or learned (see appendix I). The study had babies get on a platform and observed if they would cross the glass on top of the deep end of the apparatus. Overall, the babies didnt cross onto the glass indicating a sense of depth perception at a young age. The article also talked about the other animals experience on the visual cliff as well as future applications of their research this became extremely beneficial when creating questions with higher level thinking skills. The article was of moderate difficulty and was approved by Ms. Sorise. The students were also given a Revised Blooms Taxonomy-styled test (see appendix II). Each level of the educational taxonomy had three questions on the test associated with it (a total of 18 questions). The first five levels of the taxonomy were expressed as multi-choice questions on the test (each with four answer choices), while the highest level, creating, were short answer questions. All questions were written based off question stems for each level. The order of the question levels appeared randomly on the test; however, the creating questions or short answer questions were located at the end of the test. A pilot study was conducted on Dr. Truglios research methods class to check the validity of the test. This was supported with a Cronbachs alpha value of 0.64. Once the test was completed, students were then given a survey to fill out. The survey asked five questions with 1 to 7 likert scale ratings. This survey assessed students motivation and seriousness during the study; the purpose of this, was to see if there were any outliers who didnt care about the task. ConditionsThis study had three conditions: the expectation to take a test, the expectation to teach, and no expectation. When the articles were handed out, depending on which class period, the teacher told them if 1) they had to take a test the next day, 2) they had to teach the material to another student or 3) nothing at all mimicking a pop quiz scenario. Those who expected to take a test the next day were told that the score they got on the test would determine the number of raffle tickets they would get for a prize. Those expecting to teach were also told that they would be teaching a specific section of the paper (told that it was assigned randomly on the next day) to another student, to decrease stress for the student. Additionally, those expecting to teach were told that the person they teach would be taking a test, and that their score would determine how many raffle tickets the participant got. The no expectation group (the control group) were not aware of the motivation factor until the test was given out.ProceduresThe study was conducted over two days (total of 50 minutes). All subjects were given instructions based off their conditions listed above. Subjects were then given 20 minutes to read the article on the Visual Cliff. They were given a sheet of paper attached to the article if they wanted to take notes or prepare however they like. They were also allowed to write and make marking on the article. Subjects were required to mimic testing conditions, in which cellphones and talking was prohibited during the time of the study. The article was then collected at the end of the 20 minutes; their articles had their names on it, so they could have it back the next day. The next day, students were allowed another 10 minutes to refresh their memory of the article. The purpose of this was so students wouldnt have to recall information for their assessment. After 10 minutes, regardless of condition, all students were told to clear off their desks and put away their material for a test. All conditions were given 30 minutes to complete the 18 question test. The multiple choice answers were to be filled out on a scantron. The test required a students subject number so privacy would be maintained. No extra time was given to complete the test. Once the test was completed, students were then given the survey to assess their seriousness and motivation during the study. Scoring Each question on the test was worth three points (total points on the test =54). The multi-choice questions were graded with a scantron machine, then hand graded to see if any mistakes were made. The short answer was graded based off a rubric. The rubric was given to another student for them to grade our short answer question responses (blindly graded). For the overall score, we added up the total number of points the student earned. We also noted how many points they earned for each level (A maximum of 9 points), as well as the average number of points they earned for the multiple choice (again average of 9 points), and the average number of points they earned for the short answer level. The teacher collected back the articles, and we decided to quantify their marking and writing on the article. Our first measure was to see the number of annotations made on the article and extra sheet of the paper. We defined annotations as different ideas written down by the student. We also took note of the word count the number of words written down on the article and sheet of paper. We then counted the number of sentences underlined or highlighted on the article. This, along with the test scores and Likert scale responses for each question, was organized into data tables for analyses. ResultsIn order to test the hypothesis, an experiment was created in which students were given different expectations on how they were being assessed on the article we gave them. Depending on their class, the students were expected to take a test, expected to teach to another student, or had no expectation. Regardless of condition, all students were given an 18 question Blooms taxonomy-styled test with 15 multiple choice questions and 3 short answers (each question is worth three points). The students were also given a survey that had 5 questions with a 1 to 7 Likert scale. Lastly, we viewed their articles and counted the number of people who annotated in each condition. All statistical tests were conducted using PSPP.Average Test Score in Each ConditionAn ANOVA test was used to compare the total points earned (out of 54 points) in each condition (Figure 1). For the expecting to teach condition, the mean was 40.125 (SE=1.455); for the expecting to take a test condition, the mean was 37.961 (SE= 1.749); finally, for the no expectation condition the mean test score was 35.529 (SE= 1.615). The sample sizes were 24, 26, and 17 respectively. There was no significance difference found among these conditions average test scores (F=1.56; p >0.05).Figure 1. This graph indicates the average total of points earned in each condition. The means have been reported above each condition and the bars represent standard error. Average Score in Each Question TypeNext, we compared the average number of points in multiple choices questions (the average of the first five levels) and short answer questions (average of the creating questions) in each condition using ANOVA with Tukeys post hoc. For the multiple choice questions the means were the following: the expecting to teach condition had an average of 6.7 points (SE=0.26), the expecting to take a test condition scored an average of also 6.7 points (SE= 0.32), and the no expectation condition scored an average of 6.4 points (SE= 0.28). When comparing the average points earned in the multiple choice questions for all the conditions, there was no significant difference (F= 1.45; p>0.05). For the short answer question, the average points earned were the following: the expecting to teach condition had a mean of 6.1 (SE= 0.45), the expecting to take a test condition scored an average of 4.3 (SE= 0.59), and the no expectation had a mean of 3.2 (SE= 0.61). There was a significant difference among all the conditions (F=4.70; p=0.012), as well as between conditions. There was a significant difference between the expecting to teach group and the expecting to take a test group (p