Teaching as a Chemistry Laboratory Graduate ... - ACS Publications

Article Cite This: J. Chem. Educ. XXXX, XXX, XXX-XXX

pubs.acs.org/jchemeduc

Evaluating the Impact of the “Teaching as a Chemistry Laboratory Graduate Teaching Assistant” Program on Cognitive and Psychomotor Verbal Interactions in the Laboratory A. Flaherty,* A. O’Dwyer, P. Mannix-McNamara, and J. J. Leahy EPI*STEM National Centre for STEM Education, University of Limerick, Limerick V94 T9PX, Ireland S Supporting Information *

ABSTRACT: Designing and evaluating teacher development programs for graduate teaching assistants (GTAs) who teach in the laboratory is a prominent feature of chemistry education research. However, few studies have investigated the impact of a GTA teacher development program on the verbal interactions between participating GTAs and students in the undergraduate laboratory. Further, little research has been devoted to the development of an instructional model designed specifically for GTAs. This research set out to develop an instructional model to underpin a GTA teacher development program and to evaluate its impact on the cognitive and psychomotor verbal interactions between GTAs and students in the laboratory. Seven GTAs participated in the Teaching as a Chemistry Laboratory Graduate Teaching Assistant (TCL-GTA) program that featured the development and implementation of the Meaningf ul Learning in the Laboratory (MLL) instructional model seeking to nurture undergraduate students’ cognitive, psychomotor, and affective domains of learning. The verbal interactions between each GTA and the students they interacted with were audio recorded for the entire duration of general chemistry laboratory sessions that took place before, during, and after the TCL-GTA program. The purpose of this article is to explore the influence of the TCL-GTA program on the cognitive and psychomotor verbal interactions between GTAs and undergraduate students during general chemistry laboratory sessions. KEYWORDS: Chemical Education Research, First-Year Undergraduate/General, Graduate Education/Research, Laboratory Instruction, Collaborative/Cooperative Learning FEATURE: Chemical Education Research

■

PURPOSE The purpose of this study was to develop a research-informed instructional model to underpin a graduate teaching assistant (GTA) teacher development program and to evaluate the impact of the program on the cognitive and psychomotor verbal interactions between GTAs with students in the laboratory. Here, cognitive verbal interactions refer to students’ understanding of experimental calculations, reactions, and procedures while psychomotor verbal interactions refer to the practical aspects of competing laboratory activities and maintaining laboratory safety standards.

■

The evaluation of these programs provide evidence for advancements in GTAs’ pedagogical chemical knowledge,1 ability to lead a prelaboratory discussion before noninquiry laboratory sessions,9 content knowledge to teach,3 confidence to teach,8 and ability to employ innovative teaching methods.5 These program evaluations also extend to students’ positive perceptions of GTAs’ ability to lead undergraduate studentcentered recitations,7 level of preparedness, understanding of material, clarity of explanation and encouragement to develop thinking and problem solving skills,6 and use of effective instructional strategies.2 Most of these evaluations have relied on observation analyses,1,2,9 interviews with faculty and participating GTAs,4,7,9 GTA surveys and questionnaires,3,6−8 student surveys and questionnaires,5−7 and comparison of students’ terminal course exam scores.2 A review of the literature associated with the development of GTAs’ teaching capabilities reveals two gaps. First, to our knowledge, no study has investigated the impact of a GTA

LITERATURE REVIEW

GTA Teacher Development

GTAs are crucial components of teaching and learning processes adopted throughout undergraduate laboratories as they are often responsible for promoting safety, providing directions, developing procedural skills, as well as teaching chemical concepts.1 A number of teacher development programs have been developed and evaluated in order to develop the instructional capabilities of chemistry GTAs.1−9 © XXXX American Chemical Society and Division of Chemical Education, Inc.

Received: May 31, 2017 Revised: September 10, 2017

A

DOI: 10.1021/acs.jchemed.7b00370 J. Chem. Educ. XXXX, XXX, XXX−XXX

Journal of Chemical Education

Article

concept understanding tests,34−37 misconception tests,38 science reasoning tests,39 process skills tests,34,35 perceptions of learning tests,37 and attitudes toward science tests.36,38 Other methods of analyses include analyzing the responses of students and course leaders during interviews,35,37 the responses made by students throughout their reflective journals,37 and classroom observations and video recordings.39 Predict−Observe−Explain (POE) Technique. The POE technique presents students with a physical phenomenon asking them to make a prediction of what they anticipate will happen when an action occurs.14,23,24,40 Then, students must explain any discrepancies in their initial predictions.24 The POE technique is considered to be a useful tool in diagnosing students’ understanding of science and in identifying their levels of achievement in the chemistry laboratory.41 The POE technique was subsequently adapted into two other instructional models: the predict−discuss−explain−observe−discuss− explain teaching strategy (PDEODE)42,43 and the model− observe−reflect−explain (MORE) thinking frame.15,16,44,45 Methods of evaluating the impact of POE techniques include students’ written responses; interviews with individual students; portfolios and journals of students;41,46 student interviews; pre-, post-, and delayed postconceptual tests;42 and analysis of students’ written descriptions as models of their ideas about the behavior of electrolytes and nonelectrolytes in aqueous solutions.44 Peer-Led Teaching and Learning Techniques. Given the emphasis placed on the social aspects of learning,47 it is reported that peers are often better catalysts for learning than superiors.48,49 This is particularly fitting in the context of the undergraduate laboratory as GTAs interact with students in promoting safety, providing directions, developing procedural skills, as well as teaching chemical concepts.1 In order to accentuate the positive influence that students’ peers have on their learning experiences, various different peer-led teaching and learning techniques have been developed and implemented accordingly.20−22,50−55 Methods of evaluating the impact of various peer-led teaching and learning techniques include analyzing differences in terminal course grades,20,21,50−54 student surveys,21,50,51,53,56 student interviews,22,50 student attendance and retention rates,21,50−53 laboratory video recordings,56 and the nature of students’ exam answers.55 To summarize, studies evidencing the positive contributions of these various instructional models in helping faculty to inform instructional decisions in science have used a range of research methodologies. From this literature review, frequently used methodologies include analyses of students’ test scores,20,21,26−29,34−39,50−54 laboratory reports, reflective journals and the nature of their exam answers,25,32,46,55 interview responses,22,29,41,50 survey responses,21,22,31,36−38,50,51,53 attendance and retention rates,21,50−53 and general observational tools.22,26,27 However, only one of the cited studies investigated the impact of the SWH approach on students’ verbal interactions in an elementary teaching and learning context.30 Given how crucial GTAs are in contributing to students’ laboratory learning experiences,1,12,57,58 understanding how they verbally interact with students is important. Therefore, the purpose of this study was to develop an instructional model that would underpin a GTA teacher development program and to evaluate its impact on cognitive and psychomotor verbal interactions between GTAs and students in the laboratory.

teacher development program on all of the verbal interactions each individual participating GTA has with students in the laboratory throughout the duration of the teacher development program. A handful of studies have provided insight into the nature of verbal interactions between GTAs and students during inquiry-based general chemistry laboratory sessions10,11 as well as during one noninquiry general chemistry laboratory session.12 During extended open-inquiry laboratory activities, students interacted less with GTAs compared to students completing noninquiry laboratory activities, claiming a change in GTA behavior from a deliverer to a facilitator of information.10 However, in another study, students sought more help from laboratory teaching assistants (TAs) and interacted with TAs more as a function of their cognitive processing during open-inquiry laboratory activities compared to verification laboratory activities.11 More recently, a study analyzing the behaviors of TAs as well as their verbal interactions with students during one noninquiry general chemistry laboratory session classified four different TA instructional styles.12 The “waiters” are described as TAs who wait for students to call on them for assistance and initiate few interactions with students. The “busy bees” are described as TAs who are persistently called upon by students but do not initiate a considerable amount of interactions with students. The “observers” are the TAs who spend most of their time in the laboratory observing students. The “guides on the sides” are described as TAs who engage and initiate interactions with students in an effort to praise and probe for students’ understanding. Students’ behaviors that included performing laboratory activities, asking TAs questions, and initiating interactions were found to be independent of the TAs’ instructional styles.12 The second gap in the literature is associated with a shortage of laboratory instructional models that guides faculty in making instructional decisions.13 Specific to this research study, there is a lack of instructional models for GTAs that guides them in conceptualizing how students learn and how GTAs can use this model to inform how they instruct students in the laboratory. Some existing instructional models that can guide faculty in making instructional decisions include the science writing heuristic, the 5E learning cycle, the predict−observe−explain techniques, and various peer-led teaching and learning techniques.14−24 In order to develop and evaluate an instructional model for GTAs, literature studies associated with the nature of each aforementioned instructional model as well as the methods used to evaluate its impact on teaching and learning science will be explored. Laboratory Instructional Models

Science Writing Heuristic (SWH). Toward the generation of scientific understanding, the SWH aims to capitalize on the power of writing in order to promote students’ conceptual understanding of laboratory investigations.25 Methods of evaluating the impact of the SWH include various language and science tests,26−29 classroom observations,26,27 classroom audio recordings,30 student surveys,31 students’ laboratory reports,25,32 and student interviews.29 The 5E Learning Cycle. Informed by the Science Curriculum Improvement Study learning cycle,33 the 5E learning cycle is a teaching and learning procedure that consists of five phases: engagement, exploration, explanation, elaboration, and evaluation.17 Methods of evaluating the impact of the 5E learning cycle include analyzing students’ test scores on B



Article

Figure 1. MLL instructional model.

■

MLL INSTRUCTIONAL MODEL Research pertaining to the contributions of various meaningful learning theories throughout chemistry education research59−65 informed the development and implementation of the Meaningf ul Learning in the Laboratory (MLL) instructional model for GTAs.

meaningful learning have recently drawn considerable attention from the chemistry education research community.61,63−65,68,69 A prominent theme throughout this area of chemical education research is the significance of students’ affective learning experiences in the laboratory.63−65 Feeling good by completing laboratory requirements as well as finishing such requirements early is an affective goal that overrules students’ cognitive and psychomotor learning goals in the laboratory.63 Although recognition of the significance of affective laboratory learning experiences is growing, faculty have reported placing less emphasis on affective laboratory learning goals in comparison to cognitive and psychomotor laboratory learning goals.69 This literature contributed to the development of the MLL instructional model in the following ways: • Toward the construction of new knowledge, ascertaining what students already know is important. • Toward the establishment of meaningful learning conditions in the laboratory, students’ affective, cognitive, and psychomotor learning domains must be stimulated. • Toward the establishment of nurturing learning conditions in the laboratory, particular emphasis needs to identify and address students’ affective learning domain. Therefore, as illustrated in Figure 1, the MLL instructional model is composed of six questions. Through collectively engaging with each question throughout open discussions

Meaningful Learning

With roots in the constructivist approach to learning, Ausubel’s assimilation theory claims that learning is composed of a process of assimilating new concepts and propositions into existing conceptual and propositional frameworks.60,66,67 As such, learning that involves the connection of new concepts to existing prior knowledge is deemed to be a meaningful learning experience. This theory of meaningful learning is contrasted against rote learning that simply involves the memorization of new concepts.60,61,67 The significance of students’ prior knowledge is reflected in the emphasis that is placed on the role of the teacher exploring what students already know in a number of the instructional models reviewed in this article that include the SWH, 5E learning cycle and various POE techniques. Ausubel’s theory of meaningful learning strongly influenced Novak’s theory of meaningful learning.61 Novak built upon Ausubel’s theory of meaningful learning to involve “the integration of students’ affective, cognitive and psychomotor domains of learning”.59 Ausubel and Novak’s theories of C



Article

spoken by the remaining three graduate students. Prior to this research, all graduate students involved in undergraduate laboratory sessions at the institution that hosted this research were initially referred to as “laboratory demonstrators”. However, the researchers made the decision to address graduate students as graduate teaching assistants (GTAs) for the duration of this research in order to acknowledge the graduate students’ capacity as “teachers” and not as “demonstrators”. Prior to the TCL-GTA program, the GTAs had no formal teacher development experience. GTAs were required to attend 6 h of undergraduate laboratory sessions per week. The GTAs did not give prelaboratory lectures; they did not have any input in the pedagogical approach that was employed and did not teach outside of the laboratory such as course recitations. GTAs attended a safety briefing before they commenced their roles as GTAs. A traditional, noninquiry approach to teaching and learning was employed throughout general chemistry laboratory sessions at this institution. An average of five GTAs attended each laboratory session whereby their main responsibility was to maintain safety, help students when necessary, and sign their laboratory reports at the end of the session. All laboratory reports were assessed by the course leaders and not by the GTAs at the end of every laboratory session. An average of 50 students of mixed ability attended each laboratory session and worked in pairs to complete the laboratory requirements. The GTA and student assignment to each laboratory session time slot did not change for the remainder of the semester. Students were not required to have prerequisite chemistry knowledge or laboratory experience in order to enroll in the first year, general chemistry course and therefore, the relative experience of students in the laboratory was vast. However, this research study took place in the second semester of the general chemistry course meaning that most students had the experience of carrying out titrimetric volumetric analyses from their first semester of general chemistry. Prior to this research, GTAs and students did not know each other.

during a teacher development program, the MLL instructional model seeks to guide GTAs’ conceptualization of how students learn in a meaningful manner in order to inform how they interact and instruct students in the laboratory. Two questions are devoted to students’ affective, cognitive, and psychomotor learning experiences and outcomes for a particular laboratory session. For each of the two questions, one question explores students’ prior knowledge and experiences and the second question sets out the goals for students’ learning during one particular laboratory session in each of their three respective learning domains. The first question related to student’s psychomotor learning domain asks GTAs to discuss the practical skills they think students have experience of before a particular laboratory session. The second question then asks GTAs to discuss the practical skills that they think students should develop during a particular laboratory session. A specific aim of the MLL instructional model is to encourage GTAs to integrate greater levels of conceptual discussion with students as a feature of students’ cognitive learning experiences. Therefore, the first question related to students’ cognitive learning domain asks GTAs to discuss what they think students will know about what they see on a conceptual level before a particular laboratory session. The second question then asks GTAs to discuss what they think students should understand about what they see on a conceptual level during a particular laboratory session. In line with recent literature studies providing evidence for the significance of students’ affective laboratory learning experiences,63−65 the two affective MLL questions are illustrated in Figure 1 to supersede the psychomotor and cognitive MLL questions. The first question related to students’ affective learning domain asks GTAs to discuss how they think students will feel before a particular laboratory session based on the presentation of literature reporting to students’ affective laboratory learning experiences. The second question then asks GTAs to discuss how they think students could feel at the end of a particular laboratory session. The MLL instructional model is distinct from the other science instructional models reviewed in this article as it specifically seeks to guide GTAs in conceptualizing how students learn in a meaningful manner in order to inform how they interact and instruct students in the laboratory. However, similar to the SWH, the 5E learning cycle and the predict−observe−explain techniques, the MLL instructional model emphasizes the significance of students’ prior knowledge while leveraging the positive contributions of the social constructivist paradigm that provides the premise for the various peer-led teaching and learning techniques in considering GTAs’ and students’ closely related virtues of age and student status.

■

Ethics

Ethical approval for this study was granted by the ethical committee at the institution that hosted this research. The anonymity of all participants involved in this research was ensured through the use of pseudonyms, and all of the data collected was made confidential. All of the participating GTAs and students signed consent forms after information sheets detailing the nature of this research were distributed to each participant. Opportunities to cease participation in the research at any stage were afforded to participants. It was also emphasized to students that their participation would not be used to assess their chemical knowledge, skills, or performance in the general chemistry course.

METHODOLOGY

Participants

Teaching as a Laboratory Graduate Teaching Assistant Program

In order to recruit graduate students to participate in this research, a presentation detailing the objectives of this research was made to graduate students who assisted in the general chemistry laboratory. Participation in this research was voluntary, and four female and three male graduate students, ranging in age from 23 to 34 with at least one year of experience in assisting in the delivery of general chemistry laboratory sessions, agreed to participate. English was the native language of four of the participating graduate students while Telugu, Hungarian, and Spanish were the native languages

The TCL-GTA program featured the implementation of the MLL instructional model as well as the simultaneous enhancement of GTAs’ sense of psychological empowerment70 as laboratory instructors.71 As described in another paper associated with this research,71 psychological empowerment is a construct that manifests in four intrinsic motivational cognitions including the sense of impact, competency, autonomy, and meaningfulness experienced by an individual. Prior to the TCL-GTA program, GTAs did not perceive a sense of impact, competency, autonomy, and meaningfulness in their D



Article

Figure 2. Timeline of when the TCL-GTA opening seminar and workshops took place relative to each stage of data collection.

Data Collection

roles as laboratory instructors because they did not see themselves as effective teachers with the capability to influence what students learned.71 In an effort to enhance the sense of psychological empowerment experienced by GTAs, the authors designed and implemented the TCL-GTA program in order to nurture authentic pedagogy, which posits making decisions on the basis of standards of intellectual quality rather than teaching techniques or processes72 among GTAs by developing a professional teaching community who had a collective responsibility for undergraduate students’ learning.71,73 Here, the TCL-GTA program involved an opening seminar followed by a four consecutive workshops. During the opening seminar, the program facilitator introduced GTAs to three areas of chemical educational research: the learning difficulties faced by students in the laboratory, 7 4 −8 1 meaningful learning,61,62,64,65,68,69,82 and literature purporting to the positive impact that GTAs can have to the laboratory learning environment.1,57,58,83−85 Following the opening seminar, four consecutive workshops took place in the intervening weeks of four different general chemistry laboratory sessions, scheduled on a fortnightly basis (Figure 2). During the workshops, GTAs sat around a round table and openly discussed their ideas and opinions to each MLL question based on one particular general chemistry laboratory session in line with the tenant of authentic pedagogy. Diverse prior learning experiences and areas of research expertise led each GTAs to develop different opinions to each of the MLL questions. Nevertheless, the program facilitator encouraged GTAs to strive to achieve the learning outcomes they felt were most important for the students to achieve. The researchers believed that if GTAs were encouraged to pursue the learning outcomes which felt most strongly about, there was a greater chance that GTAs may actively pursue the achievement of such student learning outcomes throughout their verbal interactions with students in the laboratory.

The verbal interactions between individual GTAs and individual students were audio recorded at three stages in the research, stages 1, 2, and 3, by placing dictaphones in the laboratory coats of each of the seven GTAs who were participating in the TCL-GTA program. Figure 2 provides a description of when the three stages of data collection occurred with each GTA and in what laboratory sessions, relative to the TCL-GTA opening seminar and four consecutive workshops. Stage 1 involved all of the GTAs being recorded in a noninquiry, second semester general chemistry laboratory session based on identifying ionic and covalent bond types and properties of solids that took place before the TCL-GTA program began. Stage 2 involved all of the GTAs recorded in a noninquiry, second semester general chemistry laboratory session featuring the analyses of household products using titrimetric methods of experimentation that took place after the second TCL-GTA workshop. Due to scheduling constraints, some GTAs could not attend the final noninquiry, second semester rates of reactions general chemistry laboratory session that took place after the fourth TCL-GTA program. Therefore, stage 3 of data collection entailed GTAs being recorded in alternate laboratory sessions as described in Figure 2. The duration of recordings for all seven GTAs lasted 10.65 h during stage 1, 12.64 h during stage 2, and 13.51 h during stage 3. The principal researcher immediately transcribed the audio recordings, and the collaborating researchers involved in this study confirmed the transcription accuracy. The principal researcher also took field notes and wrote reflections after the completion of each workshop. Data Analysis

The transcriptions of audio recordings from each of the three stages of this research were used to analyze the impact of the TCL-GTA program on the cognitive and psychomotor verbal interactions between GTAs and students in the laboratory. In E



Article

Table 1. Name, Description, and Example of Each Tertiary Category Associated with GTAs’ Cognitive Interactions Category Type Primary Secondary Tertiary

Secondary Tertiary

Description Cognitive GTA interactions Asking cognitive questions Abstract concept question Procedure concept question Observation question Observation concept question Data analysis question Data analysis concept question Providing cognitive explanations Abstract concept explanation Substance explanation Apparatus explanation Procedure explanation Procedure concept explanation Observation explanation Observation concept explanation Data analysis explanation/instruction Data analysis concept explanation/instruction Lab report instruction/advice

Tertiary Category Example

Questions based on abstract chemical concepts that do not relate to observable events or to the practical features of procedures: “What does exothermic mean?” “What is a neutralization reaction?” Questions that integrate a chemical concept and a purpose and/or mechanics of the steps of a procedure: “How do you produce iodine by mixing the two solutions?” “How are we measuring enzyme activity?” Questions based on an observable event such as a color change, a phase transitions or measurement: “What was the color in the beginning?” “What did it smell like?” Questions that integrate a chemical concept and an observable event such as a color change, a phase transition or measurement: “Why do some compounds smell?” “Why is it dissolving faster?” Questions based on the numerical interpretation of experimental data using various mathematical calculations and techniques: “How can you f ind the number of moles?” “What was the molarity f rom your calculations?” Questions that integrate a chemical concept and the numerical interpretation of experimental data using various mathematical calculations and techniques: “What value is x when it is a f irst-order reaction?” “If 90% of the substance is sodium carbonate, what is the remaining 10% made up of ?”

Explanations based on abstract chemical concepts that do not relate to observable events or to the practical features of procedures: “A catalyst is something that can alter the rate of reaction.” Explanations based on the chemical and physical properties of a substance: “Potassium iodide is made up of the elements Potassium and iodine.” “This is dilute acid.” Explanations based on how a piece of apparatus functions: “When you touch the ends, the circuit will be complete and the bulb should light.” Explanations based on purpose and/or mechanics of the steps of a procedure: “You need to make the dilutions f irst then titrate them.” “You add the cold water 10 minutes af ter the color change has occurred.” Explanations that integrate a chemical concept and the purpose and/or mechanics of the steps of a procedure: “You add the persulfate and the potassium iodide together f irst so that the iodine f rom the potassium iodide can be liberated.” Explanations based on an observable event such as a color change, a phase transition, or measurement: “The color should change to colorless.” “You should see steam coming of f the sample.” Explanations that integrate a chemical concept and an observable event such as a color change, a phase transition, or a measurement: “That color change indicates that an acid and a base has interacting suf f iciently to result in the formation of a salt and water.” Explanations and instructions based on the numerical interpretation of experimental data using various mathematical calculations and techniques: “You did this part of the calculation wrong.” “You divide this by 10.” Explanations and instructions that integrate a chemical concept and the numerical interpretation of experimental data using various mathematical calculations and techniques: “If you get a straight-line graph, that means the reaction is a f irst-order reaction.” “If one molecule is reacting with one molecule, the molarity should be same if the volumes are the same.” Explanations and advice based on format and completion of laboratory reports: “You need to label your graph.” “That’s the value that goes into this box in your results section.”

Table 2. Name, Description, and Example of Each Tertiary Category Associated with GTAs’ Psychomotor Interactions Category Type Primary Secondary Tertiary

Description Psychomotor GTA interactions Asking practical questions Procedure question Substance question Apparatus question

Secondary Tertiary

Issuing practical instructions Procedure instruction Apparatus instruction Substance instruction Procedural advice Safety

Tertiary Category Example

Questions based on the purpose and/or mechanics of the steps of a procedure: “Did you add the persulfate to the iodine?” “Did you dilute the acid?” Questions based on the use, location, and disposal of substances: “Are you looking for HCl?” “Did you use the 0.1 M solution?” “Any reagent lef t?” Questions based on the use, location, and disposal of apparatus: “Did you wash the buret caref ully?” “Do you have three conical flasks?”

Instructions related to the steps of a procedure: “Add the indicator to the conical before you start to titrate.” “Add in one drop then add in two more.” Instructions related to use, location or disposal of a piece of apparatus: “Turn the Bunsen up more.” “You can re-use that volumetric f lask for that reaction.” Instructions related to use, location, or disposal of a piece of a substance: “The solutions are in the f ume hood.” “Once you’re done, place it in the red bin.” Noncompulsory advice that assists students with the steps of a procedure: “You are using a lot of dif ferent concentrations today so you can label them if it helps.” Instructions based on the maintenance and promotion of safety standards in the laboratory: “Please use your gloves.” “Tie up your hair.” “Wear your safety glasses.”

F



Article

Table 3. Name, Description and Examples of Primary Categories of the Types of Questions Students Asked GTA Category Type Primary

Description Procedure question Abstract concept question Substance question Apparatus question Observation question Lab report question Data analysis question

Category Example Questions based on the purpose and/or mechanics of the steps of a procedure: “What do we do for step 5?” “Do we mix them?” Questions based on an abstract chemical concept that do not relate to observable events or to the practical features of procedures: “What’s a redox reaction again?” “What is an endothermic reaction?” Questions based on the use, location, and disposal of substances: “Do you know where the potassium iodide is?” “Where do we get the 0.2M acid?” Questions based on the use, location, and disposal of apparatus: “Are we using water baths?” “When it says clamp, do you just put them into this?” Questions based on an observable event such as a color change, a phase transition, or a measurement: “Is that blue enough?” “What is that substance left af ter the evaporation?” “Is that clear enough?” Questions based on the format and completion of laboratory reports: “Can I write that here?” “What goes into this box in our report?” “Is my graph ok?” Questions based on the numerical interpretation of experimental data using various mathematical calculations and techniques: “How do you do the calculations?” “How do I get the molarity?” “How do you calculate the concentration of the dilutions?”

Table 4. Comparative Increase of Cognitive Questions Asked by GTAs over Stages 1, 2, and 3 GTAs in Stage 1

GTAs in Stage 2

GTAs in Stage 3

Cognitive Question Type

n

M

SD

%

n

M

SD

%

n

M

SD

%

Abstract concept question Procedure concept question Observation question Observation concept question Data analysis question Data analysis concept question Total

2 4 81 36 0 0 123

0 1 12 5 0 0 3

0 2 7 7 0 0 6

3 3 66 29 0 0

7 23 27 21 172 11 261

1 3 4 3 25 2 6

2 5 7 6 20 2 12

3 9 10 8 66 4

87 67 58 68 93 74 447

12 10 8 10 13 11 11

20 11 5 9 14 10 12

19 15 13 15 21 17

Member Checking

evaluating the impact of the TCL-GTA program on GTAs’ cognitive and psychomotor verbal interactions with students, the employment of the constant comparison method toward the systematic generation of theory86,87 was guided by its employment in a similar study by Krystyniak and Heikkinen.10 This approach to the analysis of qualitative data involves the development of categories by (i) comparing incidents to similar incidents to form a category, (ii) integrating categories and their properties, (iii) delimiting theory, and (iv) writing the theory. NVIVO software facilitated the coding process which involved four passes of the transcriptions whereby memos were written on the cognitive and psychomotor verbal interactions that appeared to be similar in nature. For the purpose of this research, each GTA verbal interaction that served as a unit of analysis consisted of GTAs’ utterances between students’ utterances when engaged in dialogue with students. Detailed descriptions of how verbal interactions were analyzed into various categories (Tables 1 and 2) in each of the four passes of analysis can be found in the Supporting Information that accompanies this paper. For the most part, the reason students initiated interactions with GTAs was to ask them a question pertaining to various cognitive and psychomotor aspects of the laboratory session. Since these student-initiated interactions were important contributors to the overall cognitive and psychomotor verbal interactions between GTAs and students, the constant comparative method was also used to analyze the types of questions students asked GTAs. Here, comparisons of the questions students asked GTAs resulted in the development of seven different categories, representative of seven different types of student questions described in Table 3. Offtask verbal interactions that occurred between GTAs and students were rare and therefore, were not analyzed.

A member-checking process was employed in order to validate and establish credibility in the four passes of data analysis. The member-checking process involves analytic categories, interpretations, and conclusions being tested with members of the stakeholding groups from whom the data were originally collected.88 With the member-checking process, the validity procedure shifts from the researchers to the participants as researchers systematically checking and reacting to the data and final narrative.89 Before engaging in the member-checking process with the GTAs who participated in this research, the principal researcher held consultations with two education experts, one noncollaborating science education expert and one education-specific Ph.D. researcher after the second and fourth passes of data analysis. These consultations sought to confirm the accuracy of the formation of categories along with their description and assignment to specific verbal interactions throughout the transcripts. The experts examined a codebook containing descriptions and examples of the verbal interactions assigned to each category as well as a fully analyzed transcript that had all of the GTAs’ verbal interactions and student questions coded to a particular category. The experts made a number of suggestions to the principal researcher such as including the word “Instruction” in the “Data Analysis Explanation” and the “Data Analysis Concept Explanation” categories to refer to incidents where GTAs explained to students how to complete a calculation by instructing them to complete various steps of solving the calculation. After the recommendations made by both experts were addressed, each GTA who participated in this research was sent a copy of the amended codebook as well as a copy of their own fully analyzed transcript from stage three of data collection. The GTAs were asked to contribute their opinions and suggestions to improve G



Article

Table 5. Comparative Increase of Cognitive Explanations Provided by GTAs over Stages 1, 2, and 3 GTAs in Stage 1

GTAs in Stage 2

GTAs in Stage 3

Cognitive Explanation Type

n

M

SD

%

n

M

SD

%

n

M

SD

%

Abstract concept explanation Substance explanation Apparatus explanation Procedure explanation Procedure concept explanation Observation explanation Observation concept explanation Data analysis explanation/instruction Data analysis concept explanation/instruction Lab report instruction/advice Total

2 4 36 7 3 112 48 0 0 46 258

0 1 5 1 0 16 7 0 0 7 4

1 1 6 1 1 15 6 0 0 6 7

1 2 14 3 1 43 19 0 0 18

7 20 30 22 25 22 20 327 71 22 566

1 3 4 3 4 3 3 47 10 3 8

3 3 5 3 4 3 5 13 8 2 14

1 4 5 4 4 4 4 58 13 4

69 55 27 108 45 57 54 169 113 32 729

10 8 4 15 6 8 8 24 16 5 10

16 6 5 14 6 3 4 21 13 3 12

9 8 4 15 6 8 7 23 16 4

Table 6. Comparative Increase of Practical Questions Asked by GTAs over Stages 1, 2, and 3 GTAs in Stage 1

GTAs in Stage 2

GTAs in Stage 3

Psychomotor Question Type

n

M

SD

%

n

M

SD

%

n

M

SD

%

Procedure question Substance question Apparatus question Total

30 9 48 87

4 1 7 4

3 1 10 6

34 10 55

104 57 10 171

15 8 1 8

9 11 3 10

61 33 6

131 71 13 215

19 10 2 10

13 7 2 11

61 33 6

Table 7. Comparative Increase of Practical Instructions Issued by GTAs over Stages 1, 2, and 3 GTAs in Stage 1

GTAs in Stage 2

GTAs in Stage 3

Psychomotor Question Type

n

M

SD

%

n

M

SD

%

n

M

SD

%

Procedure instruction Apparatus instruction Substance instruction Procedure advice Safety Total

35 91 39 11 40 216

5 13 6 2 6 6

4 8 5 2 5 6

16 42 18 5 19

49 26 10 17 8 110

7 4 1 2 1 3

3 4 1 3 1 3

45 24 9 15 7

161 64 52 33 15 325

23 9 7 5 2 9

20 4 7 4 3 12

50 20 16 10 5

Table 8. Comparative Increase of Questions Students Asked GTAs over Stages 1, 2, and 3 Stage 1 Psychomotor Question Type Student Student Student Student Student Student Student Total

procedure question abstract concept question substance question apparatus question observation question lab report question data analysis question

Stage 2

Stage 3

n

M

SD

%

n

M

SD

%

n

M

SD

%

47 4 34 64 104 17 0 270

7 1 5 9 15 2 0 6

6 1 5 6 17 3 0 9

17 1 13 24 39 6 0

71 5 21 9 21 13 344 484

10 1 3 1 3 2 49 10

5 1 3 1 3 2 13 19

15 1 4 2 4 3 71

269 52 80 70 78 8 232 789

38 7 11 10 11 1 33 16

31 10 8 4 5 1 32 23

34 7 10 9 10 1 29

categories. For example, a GTA may have finished an abstract concept explanation by asking a student a question on the abstract concept. Such an exchange was categorized into the abstract concept explanation tertiary category as well as the abstract concept question tertiary category for GTAs’ verbal interactions. The number (n), mean (M), standard deviation (SD), and percentage (%) values of cognitive questions, cognitive explanations, practical questions, and practical instructions issued by each GTA in each laboratory sessions were counted and are represented in Tables 4−7. The total number (n), total mean (M), and total standard deviation (SD) values of all cognitive questions, cognitive explanations, practical questions, and practical instructions issued by all GTAs in each stage of data collection are represented in the

the accuracy and precision of the description of each category and the verbal interactions that were assigned to each category. Apart from one GTA who suggested one question in their transcript be categorized into another category, all of the GTAs agreed to the categorization of all of their verbal interactions and made no recommendations to improve the accuracy of the analysis. The finalized codebook that includes more comprehensive descriptions of each category and coded excerpts of each GTA transcript is available as part of the Supporting Information accompanying this article. Following the finalization of the description of every category, all of the GTAs’ verbal interactions and all of the questions students asked GTAs were assigned to a category. In some instances, verbal interactions were categorized to two H



Article

provided in stage 1 (n = 112, ±15) while data analysis explanations were the most prevalent type of cognitive explanations provided in stage 2 (n = 327, ±13) and stage 3 (n = 169, ±21).

bottom row of Tables 4−7. Questions asked by students were only coded to one primary student question category. The number (n), mean (M), standard deviation (SD), and percentage (%) values of each type of question students asked GTAs during each stage of data collection as well as the total number (n), total mean (M), and total standard deviation (SD) values of all questions students asked GTAs during each stage of data collection can be found in Table 8. More detailed results that include the number of verbal interactions categorized to each category throughout each GTA transcript in each of the three stages of data collection are available as part of the Supporting Information accompanying this article.

Impact on Psychomotor Verbal Interactions

Asking Practical Questions. Table 6 contains the total number, mean, mean, standard deviation, and percentages of practical questions asked by GTAs in stages 1, 2, and 3. The total number of practical questions asked by GTAs increased by 128 questions from stage 1 (n = 87, ±6) to stage 3 (n = 215, ±11). The number of procedure questions increased by 101 questions, and the number of substance questions increased by 62 questions from stages 1 to 3. The number of apparatus questions decreased by 35 questions. Apparatus questions were the most prevalent practical questions asked during stage 1 (n = 48, ±10) while procedural questions were the most prevalent practical questions asked during stage 2 (n = 104, ±9) and stage 3 (n = 131, ±13). Issuing Practical Instructions. Table 7 contains the number of practical instructions issued by GTAs in stages 1, 2, and 3. The total number of practical instructions issued by GTAs in stage 1 (n = 216, ±6) decreased by 106 instructions during stage 2 (n = 110, ±3). However, this subsequently rose again by 215 instructions in stage 3 (n = 325, ±12). A typical example of this trend is the number of safety instructions in stage 1 (n = 40, ±5), decreasing in stage 2 (n = 8, ±1) but increasing again in stage 3 (n = 15, ±2). The number of times GTAs offered advice to students increased from stage 1 (n = 11, ±2) to stage 3 (n = 33, ±4). Impact on Student Questioning. Table 8 contains the total number, mean, standard deviation, and percentages of the various types of questions that students asked GTAs in stage 1, 2, and 3. The total number of questions asked by students increased by 519 questions from stage 1 (n = 270, ±9) to stage 3 (n = 789, ±12). Students asked GTAs mostly observational questions in stage 1 (n = 104, ±17), data analysis questions in stage 2 (n = 344, ±13), and procedure questions in stage 3 (n = 269, ±31).

Limitations

Since the data analysis procedure employed for this particular research study focused on the quantification of verbal interactions between GTAs and students, it limits the extent to which the chemical content and duration of such verbal interactions can be explored. For instance, the data presented in this article does not indicate whether GTAs prized the construction of students’ understanding of chemical concepts upon exploring students’ prior knowledge as advocated by the MLL instructional model. Insight into the accuracy, complexity, or duration of GTAs’ explanations is also limited through the quantification of their verbal interactions. The findings documented in this article cannot claim that participating in the TCL-GTA program led GTAs to establish more meaningful learning environments for students using the MLL instructional model. Since meaningful learning entails experiencing learning within students’ cognitive, psychomotor, and affective domains,90 this article only describes the impact of the TCL-GTA program on the cognitive and psychomotor verbal interactions between GTAs and students. While only seven self-selected GTAs volunteered to participate in the TCL-GTA program, more research needs to validate the conclusions of this study.

■

FINDINGS

Impact on Cognitive Verbal Interactions

■

Asking Cognitive Questions. Table 4 contains the total number, mean, standard deviation, and percentages of cognitive questions asked by GTAs in stages 1, 2, and 3. The total number of cognitive questions asked by GTAs increased by 324 questions from stage 1 (n = 123, ±6) to stage 3 (n = 447, ±12). Specifically, the number of abstract concept, procedure concept, and data analysis concept questions increased in a linear manner. The number of observation questions that GTAs asked was highest in the stage 1 session (n = 81, ±7), and after decreasing by 54 in stage 2 (n = 27, ±7), the number rose again by 31 questions in stage 3 (n = 58, ±5). Data analysis questions were the dominant type of cognitive questions asked in stage 2 (n = 172, ±20) and in stage 3 (n = 93, ±14). Providing Cognitive Explanations. Table 5 contains the total number, mean, standard deviation, and percentages of cognitive explanations provided by GTAs in stages 1, 2, and 3. The total number of cognitive explanations provided by GTAs increased by 471 explanations from stage 1 (n = 258, ±7) to stage 3 (n = 729, ±12). Specifically, explanations in relation to abstract concepts (n = +67), substances (n = +51), procedures (n = +101), procedure concepts (n = +42), and data analysis concepts (n = +113) increased while the number of apparatus explanations decreased (n = −9) and the number of observation explanations decreased (n = −55). Observation explanations were the prevalent type of cognitive explanations

DISCUSSION

Increased Verbal Interaction

Prior to GTAs’ participation in the TCL-GTA program during stage 1, the level of verbal interaction and especially the level of conceptual verbal interaction between GTAs and students within the realms of cognitive and psychomotor domains was low. By the end of the TCL-GTA program, the level of cognitive and psychomotor verbal interaction increased. By stage 3, there was an increase in the number of cognitive questions asked, cognitive explanations provided, practical questions asked, and practical instructions issued by GTAs compared to stage 1. Participating in the TCL-GTA program prompted the GTAs to adopt a more pronounced instructional style, similar to those classified as “guides on the sides”, defined as TAs who engage and initiate interactions with students in an effort to praise and probe for students’ understanding.12 Further, students asked GTAs 519 more questions in stage 3 than they did in stage 1. However, it must be considered that as time progressed from stage 1 to stage 3, the GTAs and students were experiencing more time together and, as such, were getting to each other more. The formation of rapports between GTAs and students may have contributed to the increase in the number of verbal interactions. Features of the POE I



Article

technique14,23,24 and the MORE thinking frame15,16,44 include an emphasis placed on students’ comprehension of macroscopic properties on a conceptual level. Similarly, a specific aim of the MLL instructional model was to encourage GTAs to integrate greater levels of conceptual discussion with students as a feature of students’ cognitive learning experiences. Prior to the TCL-GTA program during stage 1, only two abstract concept questions and four procedure concept questions were asked by all seven GTAs during an identification laboratory session. Further, explanations of abstract concepts were only provided on two occasions, and explanations of procedure concepts were provided on three occasions. This finding substantiates previous research documenting the lack of conceptual verbal interaction between GTAs and students in the general chemistry laboratory.1,10,12 However, GTAs were asking observation concept questions and providing observation concept explanations in stage 1 having had no prior experience of teacher training or development. A number of factors can contribute to the lack of conceptual verbal interaction between GTAs and students in the laboratory.1 These factors include GTAs’ difficulty in understanding abstract concepts and connecting them to laboratory learning experiences, conflicting beliefs regarding their job in teaching students about concepts, the considerable energy investment required to teach concepts, as well as their lack of confidence to teach concepts.1 By the end of the TCL-GTA program, GTAs were beginning to integrate more conceptual questions and explanations into their discussions with students. The researchers are currently analyzing the nature of chemical content discussed throughout these conceptual verbal interactions and how it can contribute further insight in developing GTAs’ capability to develop students’ conceptual understanding in the laboratory.

between GTAs and students. For example, GTAs’ verbal interactions on the maintenance of safety standards was highest in stage 1 that happened to take place at the beginning of a spring semester. This may suggest that because it was the first laboratory session of a new semester, GTAs felt the need to remind students of safety standards after their winter break. Prevailing Cognitive Interactions

While previous research documents the dominance of practically focused verbal interactions involving experimental procedures, apparatus, substances, and laboratory techniques between GTAs and students in the general chemistry laboratory,10,12 GTAs in this study asked more cognitive questions than practical questions, and they also provided more cognitive explanations than procedural instructions in all stages. In order words, although GTAs may have been engaged with students in discussing procedures, equipment, and laboratory techniques, they nevertheless were doing so in a way that was seeking to develop students’ understanding of such procedures, apparatus, substances, and laboratory techniques.

■

CONCLUSION By the end of the TCL-GTA program which featured the implementation of the MLL instructional model as well as the simultaneous enhancement of GTAs’ sense of psychological empowerment70 as laboratory instructors,71 the level of verbal interaction between GTAs and students in the laboratory increased. Further, the extent of conceptual discussion between GTAs and students also increased. When interpreting these findings, readers must take into consideration that the GTAs were experiencing a process of psychological empowerment.71 If more profound teaching and learning verbal discourses between GTAs and students in the laboratory is desired, the authors wish to emphasize the importance of nurturing GTAs’ sense of psychological empowerment. GTAs’ must be aware of their inherent ability to transform students’ cognitive, psychomotor, and affective learning experiences in the laboratory. This research emphasizes the significance of GTAs as crucial components of laboratory teaching and learning processes. In just three general chemistry laboratory sessions that each averaged 2 h in duration, 7 GTAs gave 1,553 cognitive explanations, asked 831 cognitive questions, issued 651 instructions, and asked 473 practical questions while students asked them 1,543 questions.

Influence of the Nature of the Laboratory Sessions

The nature of laboratory sessions in this research influenced the types of verbal interactions between GTAs and students in three ways. First, the chemical content that underpinned each laboratory session influenced the type of verbal interactions between GTAs and students. During the identification laboratory session, a majority of GTAs’ cognitive explanations and questions and students’ questions were about observable events and properties and there were no discussions on the interpretation of experimental data using various mathematical calculations and techniques. Similarly, discussions on the interpretation of experimental data using various mathematical calculations and techniques as features of the data analysis categories of verbal interactions were most prominent during the titration laboratory session that required students to solve a number of stoichiometric calculations. Second, the pedagogical approach employed during laboratory sessions can influence the type of verbal interactions between GTAs and students. Stages 1, 2, and 3 of this research all took place during traditional, noninquiry laboratory sessions involving students’ completion of a number of procedural steps which are comprehensively described in a laboratory manual. Since previous research indicates students’ reliance on GTAs to provide more procedural assistance in verification laboratory sessions than in inquiry-based laboratory sessions,11 the verification pedagogical approach employed during stages 1, 2, and 3 may have influenced the extent of instruction issued by the GTAs. Finally, the time in which a laboratory session takes place during a semester can influence the verbal interactions

■

ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available on the ACS Publications website at DOI: 10.1021/acs.jchemed.7b00370. Codebook describing each category of cognitive and psychomotor verbal interactions and a breakdown of the number of such interactions expressed by each GTA at three stages of research (before, during, and after the TCL-GTA program), and coded excerpts of transcripts from Stage 3 for each GTA (PDF, DOCX)

■

AUTHOR INFORMATION

Corresponding Author

*E-mail: Aishling.fl[email protected]. ORCID

A. Flaherty: 0000-0002-0609-4568 J



Article

Notes

(16) Poon, C.-L.; Lee, Y.-J.; Tan, A.-L.; Lim, S. S. Knowing inquiry as practice and theory: Developing a pedagogical framework with elementary school teachers. Research in Science Education 2012, 42 (2), 303−327. (17) Bybee, R. W.; Taylor, J. A.; Gardner, A.; Van Scotter, P.; Powell, J. C.; Westbrook, A.; Landes, N. The BSCS 5E Instructional Model: Origins and Effectiveness. BSCS: Colorado Springs, CO 2006, 5, 88−98. (18) Greenbowe, T. J.; Hand, B. Introduction to the Science Writing Heuristic. In Chemists’ Guide to Effective Teaching; Pienta, N. J., Cooper, M. M., Greenbowe, T. J., Eds.; Prentice Hall: Upper Saddle River, NJ, 2005; Vol. 140. (19) Greenbowe, T. J.; Poock, J. R.; Burke, K.; Hand, B. M. Using the science writing heuristic in the general chemistry laboratory to improve students’ academic performance. J. Chem. Educ. 2007, 84 (8), 1371. (20) Farrell, J. J.; Moog, R. S.; Spencer, J. N. A Guided-Inquiry General Chemistry Course. J. Chem. Educ. 1999, 76 (4), 570. (21) Lewis, S. E.; Lewis, J. E. Departing from lectures: An evaluation of a peer-led guided inquiry alternative. J. Chem. Educ. 2005, 82 (1), 135. (22) Cooper, M. M.; Kerns, T. S. Changing the laboratory: Effects of a laboratory course on students’ attitudes and perceptions. J. Chem. Educ. 2006, 83 (9), 1356. (23) White, R.; Gunstone, R. Prediction−Observation−Explanation; The Falmer Press: London, 1992. (24) Gunstone, R. F.; White, R. T. Understanding of gravity. Sci. Educ. 1981, 65 (3), 291−299. (25) Keys, C. W.; Hand, B.; Prain, V.; Collins, S. Using the science writing heuristic as a tool for learning from laboratory investigations in secondary science. J. Res. Sci. Teach. 1999, 36 (10), 1065−1084. (26) Hand, B.; Norton-Meier, L. A.; Gunel, M.; Akkus, R. Aligning teaching to learning: A 3-year study examining the embedding of language and argumentation into elementary science classrooms. International Journal of Science and Mathematics Education 2016, 14 (5), 847−863. (27) Nam, J.; Choi, A.; Hand, B. Implementation of the science writing heuristic (SWH) approach in 8th grade science classrooms. International Journal of Science and Mathematics Education 2011, 9 (5), 1111−1133. (28) Kingir, S.; Geban, O.; Gunel, M. How does the science writing heuristic approach affect students’ performances of different academic achievement levels? A case for high school chemistry. Chem. Educ. Res. Pract. 2012, 13 (4), 428−436. (29) Hand, B.; Wallace, C. W.; Yang, E. M. Using a Science Writing Heuristic to enhance learning outcomes from laboratory activities in seventh-grade science: quantitative and qualitative aspects. International Journal of Science Education 2004, 26 (2), 131−149. (30) Cavagnetto, A.; Hand, B. M.; Norton-Meier, L. The nature of elementary student science discourse in the context of the science writing heuristic approach. International Journal of Science Education 2010, 32 (4), 427−449. (31) Putti, A. High school students’ attitudes and beliefs on using the science writing heuristic in an advanced placement chemistry class. J. Chem. Educ. 2011, 88 (4), 516−521. (32) Rudd, J. A. I.; Greenbowe, T. J.; Hand, B. M.; Legg, M. J. Using the science writing heuristic to move toward an inquiry-based laboratory curriculum: An example from physical equilibrium. J. Chem. Educ. 2001, 78 (12), 1680. (33) Karplus, R.; Thier, H. D. A New Look at Elementary School Science: Science Curriculum Improvement Study; Rand McNally: Chicago, 1967. (34) Ceylan, E.; Geban, O. Facilitating Conceptual Change in Understanding State of Matter and Solubility Concepts by Using 5E Learning Cycle Model. Hacettepe University Journal of Education 2009, 36, 41−50. (35) Yalçın, F.; Bayrakçeken, S. The effect of 5E learning model on pre-service science teachers’ achievement of acids-bases subject. International Online Journal of Educational Sciences 2010, 2 (2), 508− 531.

The authors declare no competing financial interest.

■

ACKNOWLEDGMENTS The authors would like to thank those who participated in this research, the EPI*STEM National Centre for STEM Education, Department of Chemical and Environmental Sciences, and the Centre for Teaching and Learning at the University of Limerick for their support in making this research possible. Thanks are also extended to Professor Sibel Erduran who contributed valuable insight at the beginning of this research.

■

REFERENCES

(1) Bond-Robinson, J.; Rodriques, R. A. B. Catalyzing graduate teaching assistants’ laboratory teaching through design research. J. Chem. Educ. 2006, 83 (2), 313. (2) Hampton, S. E.; Reiser, R. A. Effects of a theory-based feedback and consultation process on instruction and learning in college classrooms. Research in Higher Education 2004, 45 (5), 497−527. (3) Wheeler, L. B.; Maeng, J. L.; Chiu, J. L.; Bell, R. L. Do teaching assistants matter? Investigating relationships between teaching assistants and student outcomes in undergraduate science laboratory classes. J. Res. Sci. Teach. 2017, 54 (4), 463−492. (4) Wheeler, L. B.; Maeng, J. L.; Whitworth, B. A. Teaching assistants’ perceptions of a training to support an inquiry-based general chemistry laboratory course. Chem. Educ. Res. Pract. 2015, 16 (4), 824−842. (5) Marbach-Ad, G.; Schaefer, K. L.; Kumi, B. C.; Friedman, L. A.; Thompson, K. V.; Doyle, M. P. Development and evaluation of a prep course for chemistry graduate teaching assistants at a research university. J. Chem. Educ. 2012, 89 (7), 865−872. (6) Nurrenbern, S. C.; Mickiewicz, J. A.; Francisco, J. S. The impact of continuous instructional development on graduate and undergraduate students. J. Chem. Educ. 1999, 76 (1), 114. (7) Pentecost, T. C.; Langdon, L. S.; Asirvatham, M.; Robus, H.; Parson, R. Graduate teaching assistant training that fosters studentcentered instruction and professional development. Journal of College Science Teaching 2012, 41 (6), 68−75. (8) Richards-Babb, M.; Penn, J. H.; Withers, M. Results of a Practicum Offering Teaching-Focused Graduate Student Professional Development. J. Chem. Educ. 2014, 91 (11), 1867−1873. (9) Kurdziel, J. P.; Turner, J. A.; Luft, J. A.; Roehrig, G. H. Graduate teaching assistants and inquiry-based instruction: implications for graduate teaching assistant training. J. Chem. Educ. 2003, 80 (10), 1206. (10) Krystyniak, R. A.; Heikkinen, H. W. Analysis of verbal interactions during an extended, open-inquiry general chemistry laboratory investigation. J. Res. Sci. Teach. 2007, 44 (8), 1160−1186. (11) Xu, H.; Talanquer, V. Effect of the Level of Inquiry on Student Interactions in Chemistry Laboratories. J. Chem. Educ. 2013, 90 (1), 29−36. (12) Velasco, J. B.; Knedeisen, A.; Xue, D.; Vickrey, T. L.; Abebe, M.; Stains, M. Characterizing Instructional Practices in the Laboratory: The Laboratory Observation Protocol for Undergraduate STEM. J. Chem. Educ. 2016, 93 (7), 1191−1203. (13) Walker, J. P.; Sampson, V.; Zimmerman, C. O. Argument-driven inquiry: An introduction to a new instructional model for use in undergraduate chemistry labs. J. Chem. Educ. 2011, 88 (8), 1048− 1056. (14) Gunstone, R. F., Reconstructing theory from practical experience. In Practical Science; Woolnough, B. E., Ed.; Open University Press: Milton Keynes, U.K., 1991; pp 67−77. (15) Tien, L. T.; Rickey, D.; Stacy, A. M. The MORE thinking frame: Guiding students’ thinking in the laboratory. Journal of College Science Teaching 1999, 28 (5), 318. K



Article

(56) Cooper, M. M.; Kerns, T. S. Changing the laboratory: Effects of a laboratory course on students’ attitudes and perceptions. J. Chem. Educ. 2006, 83 (9), 1356. (57) Ryan, B. Graduate teaching assistants; critical colleagues or casual components in the undergraduate laboratory learning? An exploration of the role of the postgraduate teacher in the sciences. European Journal of Science and Mathematics Education Vol 2014, 2 (2), 99. (58) Herrington, D. G.; Nakhleh, M. B. What defines effective chemistry laboratory instruction? Teaching assistant and student perspectives. J. Chem. Educ. 2003, 80 (10), 1197. (59) Novak, J. D. Learning, Creating, and Using Knowledge: Concept Maps as Facilitative Tools in Schools and Corporations, 2nd ed.; Routledge: New York, 2010. (60) Ausubel, D. Educational Psychology: A Cognitive View; Holt, Rinehart & Winston: New York, 1968. (61) Bretz, S. L. Novak’s theory of education: Human constructivism and meaningful learning. J. Chem. Educ. 2001, 78 (8), 1107. (62) Bruck, L. B.; Towns, M.; Bretz, S. L. Faculty Perspectives of Undergraduate Chemistry Laboratory: Goals and Obstacles to Success. J. Chem. Educ. 2010, 87 (12), 1416−1424. (63) DeKorver, B. K.; Towns, M. H. General Chemistry Students’ Goals for Chemistry Laboratory Coursework. J. Chem. Educ. 2015, 92 (12), 2031−2037. (64) Galloway, K. R.; Bretz, S. L. Development of an Assessment Tool To Measure Students’ Meaningful Learning in the Undergraduate Chemistry Laboratory. J. Chem. Educ. 2015, 92 (7), 1149− 1158. (65) Galloway, K. R.; Bretz, S. L. Measuring Meaningful Learning in the Undergraduate Chemistry Laboratory: A National, Cross-Sectional Study. J. Chem. Educ. 2015, 92 (12), 2019−2030. (66) Novak, J. D.; Cañas, A. J. The Theory Underlying Concept Maps and How to Construct and Use Them. In Technical Report IHMC CmapTools 2006-01 Rev 01-2008; Florida Institute for Human and Machine Cognition: Pensacola, FL, 2008. http://cmap.ihmc.us/ docs/pdf/TheoryUnderlyingConceptMaps.pdf (accessed Aug 2017). (67) Ausubel, D. P. The Psychology of Meaningful Verbal Learning; Grune and Stratton: New York, 1963. (68) Galloway, K. R.; Malakpa, Z.; Bretz, S. L. Investigating affective experiences in the undergraduate chemistry laboratory: Students’ perceptions of control and responsibility. J. Chem. Educ. 2016, 93 (2), 227−238. (69) Bretz, S. L.; Fay, M.; Bruck, L. B.; Towns, M. H. What faculty interviews reveal about meaningful learning in the undergraduate chemistry laboratory. J. Chem. Educ. 2013, 90 (3), 281−288. (70) Spreitzer, G. M. Psychological empowerment in the workplace: Dimensions, measurement, and validation. Academy of management Journal 1995, 38 (5), 1442−1465. (71) Flaherty, A.; O’Dwyer, A.; Mannix-McNamara, P.; Leahy, J. J. The Influence of Psychological Empowerment on the Enhancement of Chemistry Laboratory Demonstrators’ Perceived Teaching Self-Image and Behaviours as Graduate Teaching Assistants. Chem. Educ. Res. Pract. 2017, 18, 710. (72) Newmann, F. M.; Marks, H. M.; Gamoran, A. Authentic pedagogy and student performance. American Journal of Education 1996, 104, 280−312. (73) Marks, H. M.; Louis, K. S. Does teacher empowerment affect the classroom? The implications of teacher empowerment for instructional practice and student academic performance. Educational evaluation and policy analysis 1997, 19 (3), 245−275. (74) Bates, G. The Role of the Laboratory in Secondary School Science Programs. In What Research Says to the Science Teacher; Rowe, M. B., Ed.; National Science Teachers Association Press: Arlington, VA, 1978; pp 55−82. (75) Blosser, P. E. A Critical Review of the Role of the Laboratory in Science Teaching; ERIC Clearinghouse for Science, Mathematics, and Environmental Education: Columbus, OH, 1980.

(36) Ercan, O. Effect of 5E learning cycle and V diagram use in general chemistry laboratories on science teacher candidates ‘attitudes, anxiety and achievement. International Journal of Social Sciences and Education 2014, 5 (1), 161−175. (37) Liu, T.-C.; Peng, H.; Wu, W.-H.; Lin, M.-S. The Effects of Mobile Natural-science Learning Based on the 5E Learning Cycle: A Case Study. Educational Technology & Society 2009, 12 (4), 344−358. (38) Balci, S.; Cakiroglu, J.; Tekkaya, C. Engagement, exploration, explanation, extension, and evaluation (5E) learning cycle and conceptual change text as learning tools. Biochem. Mol. Biol. Educ. 2006, 34 (3), 199−203. (39) Wilson, C. D.; Taylor, J. A.; Kowalski, S. M.; Carlson, J. The relative effects and equity of inquiry-based and commonplace science teaching on students’ knowledge, reasoning, and argumentation. J. Res. Sci. Teach. 2010, 47 (3), 276−301. (40) Champagne, A. B.; Klopfer, L. E.; Anderson, J. H. Factors Influencing the Learning of Classical Mechanics. Am. J. Phys. 1980, 48 (12), 1074−1079. (41) Liew, C. W.; Treagust, D. F. The Effectiveness of PredictObserve-Explain Tasks in Diagnosing Students’ Understanding of Science and in Identifying Their Levels of Achievement: Paper Presented at the Annual Meeting of the American Educational Research Association, San Diego, CA, April 13−17, 1998. ERIC Number: ED420715; http://files.eric.ed.gov/fulltext/ED420715.pdf (accessed Aug 2017). (42) Coştu, B.; Ayas, A.; Niaz, M. Promoting conceptual change in first year students’ understanding of evaporation. Chem. Educ. Res. Pract. 2010, 11 (1), 5−16. (43) Coştu, B.; Ayas, A.; Niaz, M. Investigating the effectiveness of a POE-based teaching activity on students’ understanding of condensation. Instructional Science 2012, 40 (1), 47−67. (44) Tien, L. T.; Teichert, M. A.; Rickey, D. Effectiveness of a MORE laboratory module in prompting students to revise their molecularlevel ideas about solutions. J. Chem. Educ. 2007, 84 (1), 175. (45) Mattox, A. C.; Reisner, B. A.; Rickey, D. What happens when chemical compounds are added to water? An introduction to the Model-Observe-Reflect-Explain (MORE) thinking frame. J. Chem. Educ. 2006, 83 (4), 622. (46) Liew, C. W.; Treagust, D. F. A predict-observe-explain teaching sequence for learning about students’ understanding of heat and expansion of liquids. Australian Science Teachers’ Journal 1995, 41 (1), 68−71. (47) Vygotsky, L. S. Mind in Society: The Development of Higher Psychological Processes; Harvard University Press, 1978. (48) Eberlein, T.; Kampmeier, J.; Minderhout, V.; Moog, R. S.; Platt, T.; Varma-Nelson, P.; White, H. B. Pedagogies of engagement in science. Biochem. Mol. Biol. Educ. 2008, 36 (4), 262−273. (49) Gosser, D. K.; Cracolice, M. S.; Kampmeier, J.; Roth, V.; Strozak, V. S.; Varma-Nelson, P. Peer-Led Team Learning: A Guidebook; Prentice Hall: Upper Saddle, NJ, 2001. (50) Tien, L. T.; Roth, V.; Kampmeier, J. Implementation of a peerled team learning instructional approach in an undergraduate organic chemistry course. J. Res. Sci. Teach. 2002, 39 (7), 606−632. (51) Hockings, S. C.; DeAngelis, K. J.; Frey, R. F. Peer-led team learning in general chemistry: implementation and evaluation. J. Chem. Educ. 2008, 85 (7), 990. (52) Mitchell, Y. D.; Ippolito, J.; Lewis, S. E. Evaluating Peer-Led Team Learning across the Two Semester General Chemistry Sequence. Chem. Educ. Res. Pract. 2012, 13 (3), 378−383. (53) Chan, J. Y.; Bauer, C. F. Effect of peer-led team learning (PLTL) on student achievement, attitude, and self-concept in college general chemistry in randomized and quasi experimental designs. J. Res. Sci. Teach. 2015, 52 (3), 319−346. (54) Lyle, K. S.; Robinson, W. R. A statistical evaluation: Peer-led team learning in an organic chemistry course. J. Chem. Educ. 2003, 80 (2), 132−134. (55) Golde, M. F.; McCreary, C. L.; Koeske, R. Peer instruction in the general chemistry laboratory: Assessment of student learning. J. Chem. Educ. 2006, 83 (5), 804. L



Article

(76) Hofstein, A.; Lunetta, V. N. The role of the laboratory in science teaching: Neglected aspects of research. Review of educational research 1982, 52 (2), 201−217. (77) Hofstein, A.; Lunetta, V. N. The laboratory in science education: Foundations for the twenty-first century. Sci. Educ. 2004, 88 (1), 28− 54. (78) Hawkes, S. J. Chemistry is not a laboratory science. J. Chem. Educ. 2004, 81 (9), 1257. (79) Lunetta, V. N.; Hofstein, A.; Clough, M. P. Learning and Teaching in the School Science Laboratory: An Analysis of Research, Theory, and Practice. In Handbook of Research on Science Education; Abell, S. K., Lederman, N. G., Eds.; Routledge: New York, 2007; pp 393−441. (80) Hofstein, A.; Kind, P. M., Learning in and from Science Laboratories. In Second International Handbook of Science Education; Springer: Heidelberg, 2012; pp 189−207. (81) Hodson, D. A critical look at practical work in school science. School Science Review 1990, 71 (256), 33−40. (82) Brandriet, A. R.; Ward, R. M.; Bretz, S. L. Modeling meaningful learning in chemistry using structural equation modeling. Chem. Educ. Res. Pract. 2013, 14 (4), 421−430. (83) Pickering, M. Report on the NEACT conference:″ The chemistry lab and its future″. J. Chem. Educ. 1988, 65 (5), 449. (84) Lazarowitz, R.; Tamir, P., Research on Using Laboratory Instruction in Science. In Handbook of Research on Science Teaching and Learning; Gabel, D., Ed.; Macmillan: New York, 1994; pp 94−130. (85) Nicklow, J. W.; Marikunte, S. S.; Chevalier, L. R. Balancing pedagogical and professional practice skills in the training of graduate teaching assistants. Journal of Professional Issues in Engineering Education and Practice 2007, 133 (2), 89−93. (86) Glaser, B. G. The constant comparative method of qualitative analysis. Social problems 1965, 12 (4), 436−445. (87) Glaser, B. G.; Strauss, A. L. The Discovery of Grounded Theory: Strategies for Qualitative Research; Transaction Publishers: Piscataway, NJ, 2009. (88) Lincoln, Y.; Guba, E. Naturalistic Inquiry; Sage Publications. Inc.: Newbury Park, CA, 1985. (89) Creswell, J. W.; Miller, D. L. Determining validity in qualitative inquiry. Theory into practice 2000, 39 (3), 124−130. (90) Novak, J. D. Learning, Creating, and Using Knowledge, 2nd ed.; Routledge: New York, 2010.

M


Teaching as a Chemistry Laboratory Graduate ... - ACS Publications

Recommend Documents