Interactions Between Classroom Discourse, Teacher Questioning, and Student Cognitive Engagement in Middle School Science

Transcription

1 J Sci Teacher Educ DOI /s Interactions Between Classroom Discourse, Teacher Questioning, and Student Cognitive Engagement in Middle School Science Julie B. Smart Jeff C. Marshall Ó The Association for Science Teacher Education, USA 2012 Abstract Classroom discourse can affect various aspects of student learning in science. The present study examines interactions between classroom discourse, specifically teacher questioning, and related student cognitive engagement in middle school science. Observations were conducted throughout the school year in 10 middle school science classrooms using the Electronic Quality of Inquiry Protocol, which is designed, among other things, to measure observable aspects of student cognitive engagement and discourse factors during science instruction. Results from these observations indicate positive correlations between students cognitive engagement and the following aspects of classroom discourse: questioning level, complexity of questions, questioning ecology, communication patterns, and classroom interactions. A sequential explanatory mixed-methods design provides a detailed look at each aspect of classroom discourse which showed a positive effect on student cognitive level during science instruction. Implications for classroom practice, teacher education, and professional development are discussed. Keywords Inquiry-based instruction Middle grades Discourse Teacher questioning Introduction Teacher instructional practices influence student learning in a variety of ways. Student outcomes such as achievement, motivation, and efficacy have been J. B. Smart (&) Presbyterian College, Clinton, SC 29325, USA jsmart25@gmail.com J. C. Marshall Clemson University, Clemson, SC 29634, USA marsha9@clemson.edu

2 J. B. Smart, J. C. Marshall associated with multiple aspects of teacher instructional practices in the classroom (den Brok et al. 2005; Pianta 1999). In particular, interactions between students and teachers have the potential to shape the course of student learning (Van den Oord and Rossem 2002). Verbal communication between teachers and students in classrooms shapes the learning environment by influencing the type of talk that students engage in during instruction (Gee 2001). This classroom talk, or discourse, often guides students in making meaning of science concepts (Duit and Treagust 2003). When teachers facilitate effective discourse during instruction, they support the development of student understanding and provide a forum for the development of conceptual understanding of scientific constructs (Mortimer and Scott 2003; Chin 2007). The science teacher plays a critical role in mediating this process in the context of inquiry-based instruction (Chin 2007). Specifically, teacher questioning has been identified as a critical factor in facilitating effective discourse in the classroom, especially in the area of supporting students cognitive engagement (Chin 2006; Chapin and Anderson 2003; Morge 2005; Dantonio and Paradise 1988). Discourse in Science Discourse has been broadly defined as the use of language within social contexts (Gee 2001). However, within science education research, the concept of discourse is more complex in meaning. Gee (2001) defined discourse as an interplay between words, acts, values, beliefs, attitudes, and social identities (p. 526) within a group of individuals who contribute jointly to sense-making and construction of meaning. Discourse is more than classroom talk; it is a complex interaction between teacher, students, and these individuals unique perspectives manifested in verbal communications. Early work in classroom discourse focused on the way in which the classroom teacher helps to construct norms of communication in the classroom and how these often implied rules for verbal interactions can constrict students ability to talk science (Lemke 1990). These verbal dynamics may serve as a barrier to students in taking personal ownership for the science content, in essence preventing students from making the language of science their own (Kelly and Bazerman 2003, p. 446). As the study of classroom discourse progressed, researchers focused on the notion that science teachers often situate themselves as authorities of scientific knowledge and acceptable classroom practices, thereby influencing the way in which students talk science (Moje 1997). The role of the teacher in facilitating effective classroom discourse in the science classroom continues to be a primary focus, especially in the following subcomponents: teacher questioning (i.e., level, complexity, and ecology) (Chin 2007; Morge 2005), classroom communication patterns (Burchinal et al. 2002), and classroom interactions (O Connor and McCartney 2007; Pianta 1999). Teacher Questioning As noted above, teacher questioning is a potentially integral subcomponent to achieving effective classroom discourse. However, teacher questioning in inquiry settings often differs in form and function when compared to questioning in noninquiry settings (Roth 1996; Gallas 1995). In non-inquiry contexts, questioning

3 Discourse, Questioning and Cognitive Engagement tends to focus on evaluating student knowledge in which the teacher asks a closed question. In this setting, the teacher is the source of knowledge, and students are expected to accept this based on the teacher s authority status (van Zee and Minstrell 1997). In contrast, teacher questioning in inquiry environments seeks to elicit student thought and encourage students to elaborate on their ideas (Lemke 1990). Teacher questioning is characterized by flexibility as the teacher adjusts questioning based on student responses in order to engage students in higher-order thinking (Chin 2007). In this inquiry environment, teacher questioning tends to be more open, and teacher responses are neutral rather than evaluative (Roth 1996; Gallas 1995). Lustick (2010) notes the value of utilizing specific focus questions during inquiry-based instruction; these questions are developed by the teacher with the intent of supporting student understanding as they participate in the process of scientific inquiry. Within the inquiry environment, teacher questioning is intended to encourage students to elaborate on previous answers, not to judge the correctness of those responses. Instead of ending the questioning cycle in an evaluative statement, students are encouraged to self-evaluate their answers and justify their claims (Morge 2005). By re-directing the evaluative role back to the students, the teacher establishes a climate that values justification, conjecture, and the co-construction of knowledge. Student Cognitive Factors Classroom discourse, specifically teacher questioning, has a direct impact on students cognitive processes (Chin 2006; Chapin and Anderson 2003; Morge 2005; Dantonio and Paradise 1988). In particular, teachers initial questioning and follow-up strategies can serve as scaffolding to support students construction of conceptual understandings of science concepts. The inquiry environment often requires students to interact with concepts for which they have limited prior knowledge. Coupled with the cognitive demands of problem-solving inherent in the inquiry process, students often experience increased levels of cognitive load (Kirschner et al. 2006). Researchers have noted the potential of teacher questioning to scaffold student cognition and lessen the cognitive load created within the inquiry environment (Chapin and Anderson 2003). Chin (2006) describes the notion of a cognitive ladder to scaffold student understanding by progressing from lower order to higher-order questioning. As students begin to engage with new content, teachers may employ lower-level questioning focused on recall and application. As students are ready to progress through the inquiry process, teachers can then utilize higher-order questioning focused on justification, explanation, and generalizing to alternate contexts. This scaffolding helps to support students learning and bridges the gap between student knowledge and conceptual understanding of science concepts (Chin 2006). A major distinction between student cognitive processes in inquiry versus noninquiry settings centers on teacher responses to correct answers. In a non-inquiry setting, correct answers are evaluated by the teacher as right and the questioning cycle ends abruptly (Mortimer and Scott 2003). In order to allow for the development of conceptual understandings of science concepts, classroom discourse

4 J. B. Smart, J. C. Marshall must proceed beyond the correct answer (Lampert 1990; Chin 2006). Research has shown that when teachers follow correct student responses with additional productive questioning, student cognitive levels increase as they are required to provide justification for their responses (Chapin and Anderson 2003; Chin 2007). The teacher s ability to engage in meaningful follow-up questioning that builds on correct student responses stimulates the use of various cognitive processes (Chin 2006, p. 1343) and supports students development of conceptual understandings of concepts in science. Social Cognitive Theory Social cognitive theory posits that students can act as cognitive models for their peers by verbally modeling methods of deductive reasoning and problem-solving strategies (Bandura 1997, 1989). According to this theory, vicarious learning can occur when students observe and duplicate successful strategies modeled by their peers (Bandura 1986). Effective teacher questioning can facilitate a classroom climate in which students frequently verbalize their ideas, thereby providing opportunities for vicarious learning to occur (Chin 2007). Students efficacy for learning science can also increase from vicarious experiences. In other words, listening to another student successfully explain their reasoning about a concept in science can increase other students efficacy for approaching similar tasks. Higherorder questioning allows for this open discussion of student ideas, which in turn facilitates a climate in which reasoning processes are made public and students can learn from their peers (Chapin and Anderson 2003; Bandura 1986). The purpose of the current study is to examine the role of the teacher in facilitating classroom discourse in supporting students higher-order cognitive processes within the middle school science classroom. By building on previous research on classroom discourse, teacher questioning, and related student cognitive factors, this study investigates the relationship between aspects of discourse in middle school science and student cognitive engagement. Specifically, the current study explores the following research question: (1) Which elements of teacherfacilitated discourse are most influential in supporting/facilitating/promoting high student cognitive engagement? (2) How are these elements manifested in middle school science classrooms? Method Participants Ten middle school science teachers participated in a sustained professional development (PD) experience designed to facilitate the transformation of teacher practice to more inquiry-based instruction. Participants were teaching at two middle schools (School A and School B) and were participating in a professional development program focused on improving the quality of inquiry facilitated in math and science education. Participants were all female and ranged in teaching

5 Discourse, Questioning and Cognitive Engagement Table 1 Demographics of participating schools School Total enrollment Enrollment by gender Enrollment by ethnicity Free and reduced meals School A 1,090 Male: 54 % White: 45 % 36 % Female: 45 % Hispanic: 17 % Black: 33 % Other: 4 % School B 851 Male: 53 % White: 35 % 54 % Female: 47 % Hispanic: 11 % Black: 51 % Other: 3 % experience from 1 year to 35 years (median = 17.5 years). Seven participants had earned a Masters or Masters Plus 30 h in their field; 3 participants held Bachelor of Science degrees. Demographics for School A and School B are provided in Table 1. The PD consisted of a two-week intensive summer institute, follow-up meetings throughout the school year, and frequent classroom support (at least once a month) from the research team. During the initial summer institute, teachers studied the 4Ex2 Instructional Model (Marshall et al. 2009) for inquiry-based instruction and then used the Model s framework to guide the development of standards-based exemplary lessons. The 4Ex2 Model (Marshall et al. 2009) provides a basis for planning and implementing content-embedded inquiry in math and science. The model consists of the following instructional sequence: Engage, Explore, Explain, and Extend. In addition, formative assessment and teacher reflection are integrated within each of these stages. Participants in the PD used the 4Ex2 Model to collaboratively plan exemplary lessons in math and science, implemented these lessons in their own classes, and revised lessons based on their instructional experiences and feedback from team members. Data for the current study were gathered during classroom observations during the subsequent school year as teachers were implementing these inquiry-based lessons. Data Collection and Analysis Formal observations were conducted in the classrooms of each of the participants beginning in early September and continuing through mid-april (N = 75). Even though interactions and observations occurred at least monthly for each teacher, the actual number of formal observations ranged from 4 to 12. These observations were conducted by a team of four researchers and ranged in length from 55 to 70 min, depending on the length of class periods at each school. The research team consisted of a science teacher educator, math teacher educator, and two math and science doctoral students. Prior to conducting observations, all members of the team received extensive training in using the EQUIP and conducted paired trial observations to establish interrater reliability. This process of establishing interrater reliability began with a series of training sessions in which team members viewed

6 J. B. Smart, J. C. Marshall taped science lessons and coded the lessons independently. Following these periods of independent coding, the research team compared their ratings and discussed points of discrepancy in order to establish a common interpretation of the instrument and its underlying constructs. This process of paired observations was repeated in the schools; observations were coded independently and then compared and discussed by researchers. This study followed a sequential explanatory/follow-up explanations mixedmethods design (Cresswell and Plano Clark 2007) and consisted of the following phases in data collection and analysis: (1) Quantitative Phase: collection and analysis of quantitative data using the EQUIP to measure classroom discourse factors and cognitive factors. (2) Data Mixing: identification of results from quantitative phase needing further detail and explanation (3) Qualitative Phase: thematic analysis of field notes and transcripts of classroom observations. The following sections describe the measures for each quantitative variable as well as analysis procedures of quantitative and qualitative data. Instrumentation The Electronic Quality of Inquiry Protocol (EQUIP) (Marshall et al. 2010) is a valid and highly reliable instrument designed to measure the quantity and quality of inquiry-based instruction. This observational protocol consists of 19 indicators forming five constructs (Time, Instruction, Discourse, Curriculum, and Assessment). Each scale is designed to measure specific constructs related to the quality of inquiry facilitated in the classroom. In the current study, the EQUIP observational protocol provided a measure of the quality of discourse facilitated during instruction and the cognitive level displayed by students during the lesson. Of particular interest in the present study is the EQUIP construct designed to measure aspects of classroom discourse. In the validation study (Marshall et al. 2010), the Chronbach s Alpha was determined to be (N = 102). The Discourse scale (Fig. 1) is comprised of the following factors: questioning level, V. Discourse Factors Construct Measured Pre-Inquiry (Level 1) Developing Inquiry (2) Proficient Inquiry (3) Exemplary Inquiry (4) D1. Questioning challenged students at Questioning rarely Questioning rarely challenged Questioning challenged Questioning various levels, including at the analysis challenged students above students above the students up to application or Level level or higher; level was varied to the remembering level. understanding level. analysis levels. scaffold learning. D2. Complexity of Questions D3. D4. D5. Questioning Ecology Communication Pattern Classroom Interactions Questions focused on one correct answer; typically short answer responses. Teacher lectured or engaged students in oral questioning that did not lead to discussion. Communication was controlled and directed by teacher and followed a didactic pattern. Teacher accepted answers, correcting when necessary, but rarely followed-up with further probing. Fig. 1 EQUIP Discourse Scale Questions focused mostly on one correct answer; some open response opportunities. Teacher occasionally attempted to engage students in discussions or investigations but was not successful. Communication was typically controlled and directed by teacher with occasional input from other students; mostly didactic pattern. Teacher or another student occasionally followed-up student response with further low-level probe. Questions challenged students to explain, reason, and/or justify. Teacher successfully engaged students in open-ended questions, discussions, and/or investigations. Communication was often conversational with some student questions guiding the discussion. Teacher or another student often followed-up response with engaging probe that required student to justify reasoning or evidence. Questions required students to explain, reason, and/or justify. Students were expected to critique others responses. Teacher consistently and effectively engaged students in open-ended questions, discussions, investigations, and/or reflections. Communication was consistently conversational with student questions often guiding the discussion. Teacher consistently and effectively facilitated rich classroom dialogue where evidence, assumptions, and reasoning were challenged by teacher or other students.

7 Discourse, Questioning and Cognitive Engagement complexity of questions, questioning ecology, communication pattern, and classroom interactions. In addition to receiving scores on each of these factors, an overall summative score was also assigned for the Discourse scale. The EQUIP is scored using a descriptive rubric; a detailed description is provided on the instrument for each factor for the following levels: (1) pre-inquiry, (2) developing inquiry, (3) proficient inquiry, and (4) exemplary inquiry. The EQUIP was also used to measure the cognitive level facilitated by the teacher at 5-min intervals as part of the Time construct. At each 5-min increment, the EQUIP provides a measure of the cognitive code that is most descriptive of the activity led by the teacher. These cognitive codes are as follows: 0-none 1-receipt of knowledge, 2-lower order (recall, remember, understand), 3-apply (demonstrate, modify, compare), 4-analyze/evaluate (verify, justify, interpret), and 5-create (combine, construct, develop, formulate). These levels, drawn from the revised Bloom s Taxonomy (Noble 2004) and the National Science Education Standards (NRC 1996), represent increasing levels of cognitive demand. An average cognitive level was also computed for each lesson, yielding the cognitive variable for each observation. Quantitative Analysis Internal consistency was calculated for the Discourse scale, which is comprised of the following five factors: questioning level, complexity of questions, questioning ecology, communication pattern, and classroom interactions. Multiple regression analyses were used to examine the interactions between the Discourse scale and student cognitive level, as measured by the EQUIP. Inter-item correlations were also calculated between specific Discourse factors and the total for the Discourse scale. Data Mixing After a thorough analysis of quantitative data, these results were used to identify aspects of classroom discourse that needed further explanation by the qualitative data collected during classroom observations. Using factors from the Discourse scale of the EQUIP as a guide, specific constructs were identified for further analysis. Field notes and transcripts from classroom observations were then analyzed in order to elaborate on aspects of classroom discourse that were found to be related to student cognitive factors during the quantitative phase. Qualitative Analysis In addition to EQUIP quantitative ratings, detailed field notes were taken for each classroom observation. Transcripts from audio recordings of classroom observations were also collected for analysis. In line with the sequential explanatory/follow-up explanations design of the present study, quantitative data were analyzed first and then qualitative data served an explanatory role. This analysis provided a more in-depth view of discourse variables found to be significantly related to student

8 J. B. Smart, J. C. Marshall cognitive factors in the quantitative analysis. Field notes and transcripts of classroom observations were analyzed using an a priori thematic analysis (Strauss 1987), guided by the following constructs: questioning level, complexity of questions, questioning ecology, communication pattern, and classroom interactions. In this a priori thematic analysis, each observation was coded using the constructs listed above in order to identify instances of these critical themes identified as significant during the quantitative phase of this study. These a prior themes provided a framework for analysis of the following data sources: observational field notes, quotes from audio recordings and researchers memos from observations. All data determined to align with a pre-determined theme were grouped together and further analyzed for subthemes in an attempt to better understand the critical elements of discourse that were significantly related to higher levels of students cognitive engagement in Phase One. Results Phase One: Quantitative Results Reliability Reliability (N = 75) for the discourse scale was estimated by computing the Cronbach s Alpha (0.917). Further, an examination of Cronbach s Alpha if Item Deleted suggested that all items within this scales should be retained. Multiple Regression A multiple regression analysis was conducted to evaluate how well discourse factors predicted student cognitive factors. The predictors were the five discourse factors, and the criterion variable was student cognitive level. The linear combination of discourse factors was significantly related to student cognitive level, F (5,74) = , p \ The sample multiple correlation coefficient was 0.674, indicating that approximately 45 % of the variance in student cognitive level in the sample can be accounted for by the linear combination of discourse factors. Table 1 presents the relative strength of the individual predictors. All of the bivariate correlations between discourse and student cognitive level were positive, and all discourse factors were statistically significant (p \ 0.01). These significant correlations suggest that all five discourse factors contribute to the overall regression model. Two of the partial correlations between the discourse factors [(Questioning Level (p \ 0.01) and Communication Pattern (p \ 0.05)] and student cognitive level were significant. Since the partial correlation represents the contribution of each predictor variable after the influence of the other variables has been accounted for, the results indicate that Questioning Level and Communication Pattern demonstrates the strongest predictive relationship with student cognitive level.

9 Discourse, Questioning and Cognitive Engagement Inter-Item Correlations Correlations between items were calculated for all discourse factors and the Discourse scale total. There were significant correlations between all individual discourse factors and between each individual factor and the Discourse scale total. These correlations are presented in Table 2. Data Mixing Following a sequential explanatory design (Cresswell and Plano Clark 2007), a period of data mixing followed the quantitative phase. Quantitative results from the first phase of this study found that classroom discourse was significantly related to student cognitive engagement; all factors within the Discourse scale were positively related to student cognitive factors. These results necessitated a follow-up qualitative phase in order to elaborate specific components of classroom discourse that may influence student cognitive engagement in science. The following discourse factors were identified during the quantitative analysis to guide the qualitative analysis of classroom transcripts and observational data: questioning level, complexity of questions, questioning ecology, communication pattern, and classroom interactions. These specific components of discourse were drawn directly from indicators on the EQUIP used to measure discourse in the classroom. This follow-up qualitative analysis allowed for a deeper understanding of aspects of classroom discourse that may have positive effects on student cognitive engagement in the science classroom (Table 3). Table 2 Bivariate and partial correlations for student cognitive level and discourse factors * p \ 0.05 ** p \ 0.01 *** p \ Discourse factors Bivariate correlation Partial correlation D1: questioning level 0.596*** 0.310** D2: complexity of questions 0.500*** D3: questioning ecology 0.544*** D4: communication pattern 0.604*** 0.293* D5: classroom interactions 0.510*** Table 3 Correlations between discourse factors, discourse total, and lesson total D1 2. D * 3. D * 0.706* 4. D * 0.657* 0.739* 5. D * 0.709* 0.715* 0.683* 6. DiscTotal 0.749* 0.786* 0.752* 0.819* 0.816* 7. LessonTotal 0.733* 0.810* 0.753* 0.762* 0.731* 0.862* * p \ 0.001

10 J. B. Smart, J. C. Marshall Qualitative Results A qualitative analysis of field notes and transcripts from classroom observations provided an in-depth examination of discourse factors. The following a prior themes (Strauss 1987) were identified as significant elements of discourse in the quantitative phase and subsequently served as a framework for analysis of qualitative data sources: questioning level, complexity of questions, questioning ecology, communication pattern, and classroom interactions. All qualitative data sources were analyzed for evidence of the constructs listed above and then grouped according to theme. Further analysis focused on identifying dimensions of each construct and developing descriptions of continuums for each theme. These continuums are discussed in relation to each significant theme of classroom discourse. Representative quotes cited as evidence for these themes were taken primarily from transcribed classroom audio recordings; several quotes were taken directly from field notes or researcher memos. Questioning Level An analysis of the level of teacher questioning in the classroom revealed patterns within this discourse factor. The following continuum emerged to describe the range of questioning levels evidenced by teachers during the observed science lessons: lower order? apply? analyze. Representative quotes and excerpts from field notes and transcripts of classroom observations were drawn from lessons scoring 1, 2, 3, and 4 on the EQUIP. These scores represent the following levels in reference to specific aspects of inquiry-based instruction: (1) Pre-Inquiry, (2) Developing, (3) Proficient, and (4) Exemplary. As evidenced by results from the quantitative phase, questioning level was positively related to student cognitive level. Teachers scoring higher on questioning level (3 or 4) tended to ask questions at an application level or higher. Specific examples of questioning levels along this continuum are provided in Fig. 2. Teachers scoring 1 or 2 tended to rely on questions focused on factual recall while teachers scoring 3 or 4 used questions requiring students to apply the knowledge to new situations and to analyze information in greater depth. Questions at the upper level of this continuum were more focused on higher-order cognitive processes that required students to process information at more sophisticated levels. In an inquiry lesson focusing on technological design, one participant demonstrated a consistent use of higher-order questioning within her instruction. The lesson required students to construct a package that would safely deliver a rare egg across the country in the U.S. mail system. Students were required to plan their design, construct a prototype, test this prototype, make revisions to the design, and finally construct the actual package used for mailing the egg. During the lesson, the teacher circulated around to groups and posed questions such as Why do you expect that design to work?, Why do you think this prototype failed?, What factors should you take into consideration when revising your model? Students responded with higher-order responses and maintained a high level of engagement

11 Discourse, Questioning and Cognitive Engagement Level Descriptor(s) Example Lower Order Apply Which layer of the Earth is the oldest? What is a dependent variable? What color is limestone? How is observation used in science? Why does the microscope have a cover on it? Why is it important that the procedures in a lab be in order and exact? How does the dependent variable relate to the independent variable? What do you think would happen if you added five more washers to the string in this experiment? Students make predictions. An apple core sits on the plate besides Dexter. He finished wiping his hands and puts a napkin on a plate. What can you infer? 4 Analyze How has testing your egg resulted in an improved design? What technology has to be found in order for a space elevator to work? Do you think this will happen during your lifetime? Why or why not? Fig. 2 D1: questioning level throughout the lesson. Figure 2 provides an additional quote from this lesson, which scored a 4 on the Questioning Level indicator on the Discourse scale. Complexity of Questions An analysis of the complexity of questions revealed the following continuum: focus on correct answer? focus on evidence and reasoning. These dimensions of teachers questioning complexity are detailed in Fig. 3. These examples represent a continuum from a focus on a single correct answer to an emphasis on student processes that lead to the answer. Teachers scoring 1 or 2 on this discourse factor generally focused on one correct answer, and these tended to be in the form of short answer responses. A score of 3 or 4 indicated that the teacher emphasized student processes such as justification, reasoning, and explanation. At more complex questioning levels, teachers also expected students to critique the responses of other students. A sixth-grade science lesson scoring a 4 on this indicator provided an opportunity for students to justify their responses and to critique the strategies of their peers. This lesson focused on the function of simple machines within the task of constructing a pyramid. Students were assigned the task to design a pyramid for an imaginary Egyptian pharaoh and construct a scale model of this pyramid, indicating the simple machines that would be necessary in its construction. Students were required to justify their use of simple machines in the construction plan and to evaluate the tools selected by other groups. For example, one group proposed the use of a pulley to raise bricks up to higher levels of the pyramid. The teacher encouraged other students to comment on this and a student noted that an inclined plan may be a better solution to moving the bricks since the pulley would require

12 J. B. Smart, J. C. Marshall Level Descriptor Example 1 Focus on Correct Answers One student asks: Can I just do it the way I do it best. T: If you are asked to do it one way, you do it that way. Sometimes one method is better than another method Focus on Evidence and Reasoning Teacher asks students to consider the characteristics that determine the classification of hurricanes and tropical storms. Teacher communicates that there is a single correct answer that she is seeking. I don t care about the answer. I am interested in the process. Students talking about and justifying their inferences. Teacher encouraging students to provide evidence for their inferences. Any other proposals? How many think the first conclusion is correct? How many think that the second one is correct? We are going to let this stew for a while. Teacher asks each group to share results with another group and discuss how results are same and different, and decide why there may be differences. She emphasizes that what matters is that they understand how they reached their results. Fig. 3 D2: complexity of questions materials that may not be available to the builders in ancient Egypt. The original student went on to defend his design and provide a rationale for the feasibility of obtaining the necessary materials for the pulley. Throughout this process, the teacher facilitated the discussion and redirected questions to the rest of the class to encourage additional feedback. Additional representative quotes and field notes are provided for Complexity of Questions in Fig. 3. Questioning Ecology Analysis of the classroom questioning ecology, or climate, a continuum based on teacher/student roles emerged: teacher explains? student explains. These dimensions of teachers questioning ecology are detailed in Fig. 4. These examples represent a continuum from questions followed by teacher explanations to questions designed to solicit student explanations. A score of a 1 or 2 indicated that the teacher generally lectured or used questioning that did not facilitate student discussions or responses. Teachers scoring a 3 or 4 engaged students in open-ended discussions that gave students the opportunity to reflect on investigations or activities; at times, students shared the burden of explanation with the teacher and in other instances, the students worked in peer groups or individually to respond to a posed question. At these higher levels of questioning ecology, students had the opportunity to interact with their teacher and their peers stemming from their responses to open-ended questioning. In the instances in which students offered the complete explanation, the teacher often provided scaffolding for this process through follow-up questioning or just-in-time information. During an eighth-grade science lesson, students were expected to work toward an explanation for an exploration conducted in small groups. Students were given gelatin capsules that contained a foam animal; students were then given the task to

13 Discourse, Questioning and Cognitive Engagement Level Descriptor Example 1 Teacher Explains Teacher re-states student hypotheses and corrects their errors. Other students are not given the opportunity to evaluate the hypotheses of other students. Teacher: See there is a pattern. All the sodas that had sugar in them sank. If it did not have sugar, it sank Student Explains During the conversation, teacher is guiding students to think about what differences in the sodas make a difference in what will sink or float. However, teacher goes back to the aspartame statement without giving students an opportunity to consider the alternative hypotheses. Teacher tries to get explanation from students, though they re struggling. She then summarizes and gives full explanation. She repeats demonstration Time was allowed for students to individually explore the p. table. Then, a class discussion was held to make sense of what was seen. A member of each group gets out a pulley. Together, and with the teacher s guidance, the class comes up with a definition of a pulley. Teacher questions students about why one capsule hatched more quickly. Teacher selects a student to come to the front of the class and explain that the hot water hatched the capsule more quickly Fig. 4 D3: questioning ecology try to remove the foam animal from the capsule without touching the capsule. After students spent time experimenting with different strategies, one group discovered that placing the capsule in hot water would free the foam animal. The teacher then began a series of questions to the group to scaffold their explanation of this phenomenon. Even as students drew closer to providing an accurate explanation, the teacher refrained from providing the correct explanation, instead allowing students to talk about their ideas and research the topic online. Students worked collaboratively and with available resources in order to piece together an accurate explanation for the gelatin capsule exploration. This example is represented in Fig. 4 along with additional representative quotes from lessons scoring high on this indicator. Communication Pattern The following dimensions emerged from an analysis of communication patterns during observed science lessons: controlled by teacher? guided by student questions and ideas. These dimensions of classroom communication patterns are detailed in Fig. 5. These examples represent a continuum from communication controlled explicitly by the teacher to classroom communication influenced and guided by student ideas. Teachers scoring a 1 or 2 on this indicator generally controlled the course of the lesson without considering or adjusting instruction based on student responses. A score of 3 or 4 indicated that the communication in the classroom was often conversational, with student questions contributing to the flow of the lesson. Higher scores reflected a greater emphasis on student ideas and recognition of student questions as legitimate sources for further discussion. A sixth-grade science lesson provided an example of a classroom communication pattern focused on student ideas and guided by student questions. In this lesson on

14 J. B. Smart, J. C. Marshall Level Descriptor Example 1 Controlled by teacher Now I am going to pass out a set of questions that you are to respond to relating to your model. After a few minutes the teacher reviewed these questions with the entire class, calling on students to give their answers. 2 The teacher pulls a Popsicle stick to select a student to give an example of an invention and its development.a student gives the example of a light bulb and how it originally only lasted for 3 days. Another student adds that before the light bulb people used candles. 3 Teacher is asking the students to talk about the things that they did to the string in order to make adjustments. This conversation is relating to independent and dependent variables. Teacher reminding student to talk to the class, not to the teacher. T: Explain to them what you did. Make them understand. One student gets up and demonstrates what her group did in to manipulate the length of the string. 4 Guided by student questions and ideas Teacher is writing a fact on the board that a student contributed: Aspertame is 180x s sweeter than sugar. Another student makes a hypothesis that it could be the carbonation, another student makes a hypothesis that it is the sodium. Some students noticed that some of the lemonades float and some of them sink. So they decide to go to other groups and try their water to see if that makes a differences. Fig. 5 D4: communication pattern density concepts, students were given several aluminum cans containing diet soda, regular soda, and lemonade. Students worked in groups to place their cans in large containers of water to compare the density of the cans. One student noticed that their can of lemonade floated while another can of lemonade sank. The teacher noted the student s question and directed the entire class to test their lemonade cans and explore the student s question. This question directed the remainder of the exploration, and students were still stumped as the class period ended. The teacher directed students to go home and think and the question, conduct additional research if possible and to bring their ideas to class to discuss the next day. The teacher s willingness to give value to the student s question and use it as a point of extending the laboratory activity resulted in a student-centered communication pattern in this science classroom. This example of a lesson scoring a 4 on communication pattern, as well as others, is provided in Fig. 5. Classroom Interactions An analysis of classroom interactions revealed the following continuum: didactic pattern of interaction? teacher facilitating dialogue between students. These dimensions of classroom interactions are detailed in Fig. 6. These examples represent a continuum from didactic forms of questioning to more student-centered discussions. A score of 1 or 2 indicated that the teacher did not utilize questions as a starting point for discussions, but rather judged the correctness of student answers. Teachers scoring 3 or 4 frequently followed up student responses with further questioning and placed value on reasoning and alternate explanations. As the score on this indicator increased, classroom discourse was richer, with students examining ideas in depth and challenging the ideas of others.

15 Discourse, Questioning and Cognitive Engagement Level Descriptor Example Didactic pattern of interaction Teacher calls on students to give the answers to a set of questions and then she explains the answers. 1 2 One student also followed-up with a simple clarification question for the student who is presenting. Teacher acknowledged student input during presentations. 3 When a student could not justify her inference, the teacher had other students confirm her conclusion but did not feed the student evidence for this conclusion. Instead she asked probing questions and redirected the question to the class. 4 Teacher facilitating dialogue between students Teacher brings students back together and asks them to talk about their hypotheses that they tested and what their results were. Students have tested a variety of hypotheses, including water temp., shaking the cans, they direction you put the can in the water, height of the water. Fig. 6 D5: classroom interactions A sixth-grade science classroom consistently displayed a climate of open dialogue between teacher, students, and peers. There are multiple lessons that would provide context for this classroom, but a particularly strong example comes from a unit on technological design, mentioned earlier in the section. During this unit, students worked in groups to design and improve on a prototype to mail an egg successfully across the country. Throughout this unit, the teacher consistently referred students to their peers for advice on revisions to their prototype and created a climate in which students viewed their classmates as valuable resources. On many occasions, the teacher directed students to go ask a classmate and see what they think about your ideas and posed questions such as who has an idea that could help this group reduce the weight of their design? This teacher helped to create an environment collaboration in her classroom and relayed to her students that their ideas were valuable and legitimate. Additional examples of lessons scoring high on the classroom interactions indicator are provided in Fig. 6. Discussion In the present study, quantitative and qualitative data provided a complementary framework for understanding the relationship between classroom discourse factors and student cognitive level. Though data mixing occurred between the quantitative and qualitative phases of the study, it is also necessary to interpret the overall findings from both phases of the study. Cresswell and Plano Clark (2007) suggest creating a visual matrix in order to examine how quantitative and qualitative data converge and diverge. Figure 7 presents a matrix of quantitative and qualitative data from the present study.

16 J. B. Smart, J. C. Marshall Quantitative Discourse Variables Significant Interactions with Student Cognitive Level Qualitative Category Qualitative Continuum D1: Questioning Level (r = 0.596) Questioning Level lower order apply analyze D2: Complexity of Questions (r = 0.500) Complexity of Questions D3: Questioning Ecology (r = 0.544) Questioning Ecology correct answer on evidence and reasoning teacher explains student explains focus D4: Communication Pattern ( r = 0.604) Communication Pattern D5: Classroom Interactions ( r = 0.510) Classroom Interactions controlled by teacher guided by student questions and ideas didactic pattern of interaction teacher facilitating dialogue between students Fig. 7 Visual matrix of quantitative and qualitative findings Meaningful discourse is the evolution of effective and engaging questioning that challenges and facilitates student cognitive engagement (Mortimer and Scott 2003). Results from the present study revealed two key findings regarding teacher questioning in these middle school science classroom. First, there was a direct relationship between discourse factors (questioning level, complexity of question, questioning ecology, communication pattern, and classroom interactions) and the students cognitive level during science instruction. In other words, the discourse facilitated by the teacher was a predictor of the cognitive level observed throughout the course of the lesson. The verbalization of student reasoning about science is critical within the social context of the classroom (Bandura 1986). According to social cognitive theory, students can be effective cognitive models for their peers by verbalizing their problem-solving strategies and methods of deductive reasoning. (Bandura 1997, 1989). In the present study, teacher questioning that focused on recall of basic facts or procedural understandings usually resulted in lower student cognitive levels. These lower-order questions do not allow for the discussion of problem-solving strategies and mental activities necessary to respond to more complex questions. However, when teachers utilize higher levels of questioning with more complexity, students have the opportunity to explain, justify, and rationalize within the social context of the classroom (Chin 2007). These students become cognitive models for peers, which can in turn facilitate the development of similar problem-solving strategies for these students. Another key result from the present study was the prevalence of lower-order questioning strategies within science instruction. National Science Education Standards call for an emphasis on conceptual understanding of science constructs, including providing opportunities for students to justify their ideas, conjecture, and

17 Discourse, Questioning and Cognitive Engagement consider alternative explanations (NRC 1996). Since a heavy reliance on lowerorder questioning strategies was correlated with lower cognitive levels for students, these questioning practices were directly related to students engagement with science concepts. In classrooms where higher-order questioning was observed, students also engaged at deeper levels with science concepts, formulating hypotheses and using evidence to draw conclusions about phenomenon. Lowerorder questions were generally indicative of teacher-centered instruction in which students were given information and expected to parrot back answers. Such instruction is inconsistent with the inquiry emphasis set forth by the National Science Education Standards (NRC 1996). With the emphasis of higher-order thinking skills and student reasoning and justification set forth by the National Science Education Standards, a renewed emphasis on classroom discourse, and specifically questioning strategies, is in line with these national initiatives for science education. Higher-order questioning also allows for teachers to formatively assess student understandings (Chin 2007; Morge 2005). Low-level, factual responses provide a limited basis for formative assessment by which teachers may adjust their instruction based on student understanding. Providing students with opportunities to verbally express their ideas can provide teachers with critical information about student reasoning and understanding to inform instructional adjustment to support student cognitive growth (Chin 2007). Implications for Practice The current study demonstrates the relationship between classroom discourse, specifically teacher questioning, and student cognitive level. If teachers want to encourage their students to develop deeper conceptual understanding of key science concepts and to become critical thinkers, they have a critical role to play in this process. Teachers have the unique opportunity to facilitate higher cognitive levels in their students by the questions they ask during instruction and the communication pattern they establish in their classrooms. The first step in this direction is for teachers to become reflective of their own practice. If teachers are aware of the effect that their questioning strategies can have on student cognition, they may become more attentive to this aspect of their practice. If teachers will first monitor their questioning strategies in a mindful way, they will be able to establish a benchmark in their own practice and can set goals for increasing the cognitive level of questioning and facilitate more student-centered discourse in their classrooms. One way in which teachers can begin to increase the quality of their questioning is to plan specific questions in advance of their instruction. During a fast-paced lesson, teachers may consciously struggle to increase the level of questions that they are using in their instruction. However, making student questions an important aspect of lesson planning is critical to ensuring that these questions take priority during instruction. Teachers may also incorporate higher-order questions into journaling activities followed by student discussion of their ideas. Giving students the opportunity to utilize and strengthen both written and oral expression of their

18 J. B. Smart, J. C. Marshall reasoning and justification processes provides a foundation for the effective communication of scientific ideas (Chapin and Anderson 2003; Chin 2007). Utilizing higher-order questioning and more student-centered discourse requires teachers to be more flexible in their own instructional practices. Teachers with higher levels of content knowledge may be more comfortable with the open-ended nature of tasks that require students to engage with divergent modes of thinking. If teachers are not efficacious about their own content knowledge, they may be more likely to rely on lower-order questions with a specific, pre-determined answer. Professional development programs in which teachers have an opportunity to increase their content knowledge in specific areas of science could prove beneficial to teachers efficacy for facilitating higher-order discussions in their classrooms (Marshall et al. 2009, 2010). Finally, teachers can benefit greatly from observing examples of higher-order questioning and student-centered discourse. Like students, teachers also learn through vicarious experiences, such as observing other teachers using effective questioning techniques or viewing exemplary practices through webcasts of instruction in inquiry-based science classrooms (Bandura 1986). Of course, this modeling is critical in science methods courses when pre-service teachers are learning the building blocks of their instructional repertoire. However, in-service teachers also need these opportunities to model questioning strategies after exemplary teachers. Professional development and online video clips could offer vicarious learning experiences for in-service teachers. In addition, administrators can provide support for teachers to observe the instructional practices of their peers and help form a community of mentors and co-learners within the cohort of the school. These experiences are all integral to providing teachers with resources to strengthen their questioning techniques, learn to lead student-centered discourse, and thereby facilitate higher levels of cognitive engagement in their students. References Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall. Bandura, A. (1989). Regulation of cognitive processes through perceived self-efficacy. Developmental Psychology, 25(5), Bandura, A. (1997). Self-efficacy: The exercise of control. New York: W. H. Freeman. Burchinal, M. R., Peisner-Feinberg, E., Pianta, R., & Howes, C. (2002). Development of academic skills from preschool through second grade: Family and classroom predictors of developmental trajectories. Journal of School Psychology, 40, Chapin, S. H., & Anderson, N. C. (2003). Crossing the bridge to formal proportional reasoning. Mathematics Teaching in the Middle School, 8(8), Chin, C. (2006). Classroom interaction in science: Teacher questioning and feedback to students responses. International Journal of Science Education, 28(11), Chin, C. (2007). Teacher questioning in science classrooms: Approaches that stimulate productive thinking. Journal of Research in Science Teaching, 44(6), Cresswell, J., & Plano Clark, V. (2007). Designing and conducting mixed methods research. Thousand Oaks: Sage Publications.

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