Undergraduate STEM students majoring in various science sub-disciplines (e.g. chemistry, physics, engineering) must develop strong understandings of core foundational thermodynamics concepts. The ability for course instructors and researchers to effectively refine instruction and develop interventions to support students' learning hinges on their ability to accurately gauge students' knowledge through the use of established measures. The Thermodynamics Conceptual Reasoning Inventory (TCRI) is designed to gauge undergraduate students' understanding of introductory thermodynamics concepts. The present study extends the findings of a previous publication by positioning the TCRI within the broader international literature of thermodynamics concept inventories and generating an argument for the reliability and validity of TCRI scores in a broader context. Participants (n = 278) took the revised 36-item TCRI (available in the supplementary online materials). Findings revealed that TCRI scores are useful in the broader context (e.g. no evidence of floor or ceiling effects, evidence of high reliability, no differences for students across majors, and TCRI scores were moderately correlated with both course exam scores and GPA). No further revisions are recommended based on analysis of item properties. The cumulative body of evidence related to the TCRI suggests that scores are useful indicators of undergraduate students' conceptual understanding of introductory thermodynamics concepts.

Lucas Passmore, Pennsylvania State University-Altoona College Lucas Passmore is an Instructor in Engineering at Penn State Altoona. He completed his Ph.D. in Engineering Mechanics in 2009. He teaches introductory engineering courses and fundamental engineering mechanics courses. His primary research is in the semiconductor device physics field, and he is currently working on the incorporation of a design element to engineering technology strength of materials course.

Fully revised to match the more traditional sequence of course materials, this full-color second edition presents the basic principles and methods of thermodynamics using a clear and engaging style and a wealth of end-of-chapter problems. It includes five new chapters on topics such as mixtures, psychometry, chemical equilibrium, and combustion, and discussion of the Second Law of Thermodynamics has been expanded and divided into two chapters, allowing instructors to introduce the topic using either the cycle analysis in Chapter 6 or the definition of entropy in Chapter 7. Online ancillaries including new LMS testbanks, a password-protected solutions manual, prepared PowerPoint lecture slides, instructional videos, and figures in electronic format are available at www.cambridge.org/thermo

NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Identifying and Remediating Difficulties with Problem-solving in Statics Abstract The work described in this paper is part of a multi-year study that seeks to enhance students’ ability to create ‘models’ successfully as they solve problems in Statics. The ultimate goal of the study is to understand the major difficulties that students encounter as they learn to model during problem-solving in Statics and to create interventions to help them more quickly overcome those difficulties. In the first phase of the study, more than 300 students completed three inventories: math skills, spatial reasoning and statics concepts. The results from the inventories were used to identify clusters of students with common characteristics, and therefore, presumably common deficiencies in their problem solving in Statics. Students from each cluster were then invited to participate in think-aloud problem solving sessions to identify the weaknesses in their problem solving. Analysis of the think-aloud sessions identified a number of common issues in students’ knowledge and ability to create models, which are summarized in the paper. Based on these findings, the research team identified possible interventions to address the common issues. Two of these interventions were developed through a design experiments process in which they were tested with groups of up to 30 students, refined to enhance their effectiveness, and then re-tested. The interventions and the development process are described, and results from the final round of the design experiments are presented. Introduction The work described in this paper is part of an on-going study of problem solving in Statics. 1,2 The work is being done in Statics classes because it is one of the first places that engineering students encounter the engineering problem-solving process. In this study we are paying particular attention to the early steps in problem-solving when students ‘model’ the system being studied to create a set of equations describing the system. In Statics students typically read a problem statement and then create a model of the system, the free-body diagram, which contains all of the salient forces on the body. Then, based on the free-body diagram, they create a mathematical model of the system. The current phase of the work is aimed at answering two main questions about the modeling processes: What are the major difficulties that students encounter when they perform modeling during problem-solving? What instructional interventions will address these problems and improve engineering students’ modeling during problem-solving? In the current phase of the work, interventions that are developed will be tested in a full-scale experimental design. Clearly there are many different ways in which students can go wrong as they solve problems in Statics. They may, for example, have inadequate knowledge of the forces and moments for particular types of connections, an inability to visualize forces, or inadequate math skills. Our working hypothesis is that students will cluster into different groups based on their abilities and knowledge, and that these groups will demonstrate differing abilities to solve Statics problems.

Fully revised to match the more traditional sequence of course materials, this full-color second edition presents the basic principles and methods of thermodynamics using a clear and engaging style and a wealth of end-of-chapter problems. It includes five new chapters on topics such as mixtures, psychometry, chemical equilibrium, and combustion, and discussion of the Second Law of Thermodynamics has been expanded and divided into two chapters, allowing instructors to introduce the topic using either the cycle analysis in Chapter 6 or the definition of entropy in Chapter 7. Online ancillaries including new LMS testbanks, a password-protected solutions manual, prepared PowerPoint lecture slides, instructional videos, and figures in electronic format are available at www.cambridge.org/thermo

His research interests include combustion-generated air pollution, other combustion-related topics, and engineering education pedagogy.

Background We tested the effects of an intervention on the learning of introductory thermodynamics principles. This intervention, OEM-Thermo, is designed to prompt the cognitive operations of meaningful learning: organization, elaboration, and monitoring. We also sought evidence to show that execution of these operations was associated with learning gains and that cognitive operations are influenced by different intervention exercises.Purpose/Hypothesis Study 1: Students who complete OEM-Thermo will gain more conceptual knowledge than students who complete traditional problems. Study 2: First, elaboration and monitoring contribute to learning with OEM-Thermo. Second, students engage in elaboration and monitoring at a higher rate when answering elaboration questions than when completing matrix exercises.Design/Method Study 1: A two-group, pre- and post-test experimental design tested OEM-Thermo effectiveness. Study 2: A one-group, pre- and post-test design where participants thought aloud while completing OEM-Thermo tested deep and surface reasoning as well as the frequency of elaboration and monitoring events.Results Study 1: A significant interaction between test time (pre- and post-test) and condition shows that OEM-Thermo promoted development of conceptual reasoning more effectively than did traditional homework problems. Study 2: Significant partial correlations were found between post-test scores on one of two deep reasoning categories and the frequency of elaboration and monitoring events in the think-aloud protocols. Differences were also found in the rate of elaboration across intervention exercises.Conclusions An intervention that includes tasks designed to stimulate the cognitive operations of meaningful learning improves students' conceptual reasoning.

Development of an Intervention to Improve Students’ Conceptual Understanding of ThermodynamicsThere is a clear need to improve students’ conceptual understanding and problem solvingabilities in thermodynamics.1, 2 In previous work, we outlined several ways that knowledge fromcognitive science could be applied to improve thermodynamics learning. The present paperdescribes an intervention that we derived from our previous work, and presents the results from apilot test of that intervention. The intervention comprises an exercise that students complete andan accompanying instructor-created video that explains how to complete the exercise. Theexercise we developed has its roots in the concept of matrix notes3, 4 because we believe thestructure of this learning strategy is well matched to the demands of thermodynamics learning.First, this structure provides an organizational framework that allows a learner to see ideas inrelation to one another; specifically, information is organized in rows and columns. In ourintervention, students consider three ideal-gas processes arranged in three rows: (i) a constant-pressure expansion, (ii) a constant-volume process in which the pressure increases, and (iii) aconstant-temperature expansion. Prompts written in the columns required students to (i) write amathematical expression of the relation of pressure to volume, (ii) write a mathematicalexpression of the relation of temperature to volume, (iii) create a plot of pressure versus volume,(iv) create a plot of temperature versus volume, and (v) to develop an expression for movingboundary work. Second, because the information that the students must supply include verbalstatements, diagrammatic depictions, and mathematical expressions, the specific format of theexercise supports the representational transformations required for thermodynamics problemsolving.5 The student is able to see, for example, how a pressure-volume plot relates to itsmathematical expression by looking across the rows of the table.We conducted a pilot test of the intervention with two sections of an introductory engineeringthermodynamics course. One section of students completed the intervention after the firstexamination and immediately before a quiz. The second section served as a business-as-usualcontrol. Scores on the first examination served as the index of prior knowledge, and quiz scoreswere the dependent variable. We anticipated that the intervention may have different effects forstudents at different levels of prior knowledge and, thus, we tested the effects of the interventionin a 2 (intervention, no intervention) by 3 (prior knowledge: low, medium, high) ANOVA. Thesignificant main effects of both prior knowledge, F(2, 95) = 14.83, p < 0.001, and theintervention were significant, F(1, 95) = 3.72, p < 0.057. The interaction between the twoindependent variables was not significant.These findings demonstrate that the intervention had a positive impact on students’ quizperformance, but two aspects of the results raise concerns. First, the significant effect of theintervention is only marginal and the effect size is rather small (partial 2 = 0.04). Second,inspection of the mean scores across prior knowledge levels show that the intervention had nobenefit for low knowledge students. We conducted think-aloud studies with thermodynamicsstudents as they completed the exercise to better understand how students were using the row-column structure. These think alouds revealed that students tended to approach the exercise in apiecemeal fashion. Although students used the organizational structure of the exercise, theytypically did not elaborate the relations across cells or monitor their understanding of theserelations. From these studies, we concluded that enhancements to the exercise were necessary,with these enhancements designed to stimulate not only the learning processes of organization,but also elaboration and metacognitive monitoring.REFERENCES1. Olds, B.M., Streveler, R.A., Miller, R.L., & Nelson, M.A., Preliminary results from the development of a concept inventory in thermal and transport science, Proceedings 2004 ASEE Conference.2. Meltzer, D., AC 2008-1505: Investigating and addressing learning difficulties in thermodynamics, Proceedings 2008 ASEE Annual Conference.3. Kiewra, K. A., Benton, S. L., Kim, S., Risch, N., and Christensen, M. (1995). Effects of notetaking format and study technique on recall and relational performance. Contemporary Educational Psychology, 20, 172–187.4. Kiewra, K. A., Dubois, N. F., Christian, D., McShane, A., Meyerhoffer, M., and Roskelley, D. (1991). Note-taking functions and techniques. Journal of Educational Psychology, 83, 240–245.5. McCracken, W.M. & Newstetter, W.C. (2001). Text to diagram to symbol: Representational transformations in problem-solving. Proceedings of the 31st ASEE/IEEE Frontiers in Education Conference, Reno, NV, pp. F2G-13 – F2G-17.

RECONSTRUCTING A THERMODYNAMICS COURSE TO BE CONSISTENT WITH WHAT WE KNOW ABOUT LEARNING ABSTRACTA common complaint of engineering educators is that students after completing a prerequisitecourse fail to retain or transfer the ideas to a subsequent course in the curriculum. Educationalpsychology research in science and related fields shows that novice learners have theirknowledge stored in pieces, whereas experts have their knowledge stored in hierarchicalstructures that allow for easy retrieval and application to familiar and to unfamiliar problems [1,2, and others]. Most engineering subjects are based on a relatively few big-picture underlyingconcepts. However, one encounters (and requires) many equations in the teaching and learningof most any engineering subject. The ability to see that many of these equations are specialcases, or are subordinate to some higher-level principle, is a major factor in distinguishingexperts from novices. Experts see the big picture and understand the key concepts that apply tothe solution of a problem. Interestingly, there is little difference between experts and novices intheir abilities to solve textbook problems, i.e., to perform well in a “plug-and-chug” mode.However, serious gaps exist between novices and experts in their conceptual understandingassociated with any given problem. We, and many others, conclude from this research thathelping students develop a deep conceptual knowledge in various engineering domains can speedtheir progress in becoming experts, i.e., skillful engineers. One approach to helping studentsachieve a higher level of conceptual understanding is the development of engineering curriculathat are integrated using a relatively few big-picture concepts. Various NSF-funded coalitions,and others, have designed curricula based on various integrating concepts [3]. For example,Richards [4] describes the design a core mechanical engineering curriculum in which ten keydefinitions and concepts perform the task of integration. Success in sustaining these curricula ismixed. An alternative to the integrated curriculum approach is to deal more explicitly withdeveloping students’ conceptual knowledge in the framework of the conventional curriculum,focusing at the course level on what are the big concepts or universal principles both within thecourse-specific domain and, more generally, within the engineering domain. This is hardly anew idea. However, seeing that students’ conceptual understanding is, in general, weak, weinvestigate in this paper how this idea can be used to guide our teaching of core engineeringsubjects. Engineering courses are by necessity equation rich. It is likely that this richness fostersa plug-and-chug approach to solving problems. In spite of there being many equations, mostsubject areas can be parsed to reveal a relatively small number of overriding concepts orprinciples. One useful goal is to create a minimum set of concepts or categories that can beeasily assimilated by students. We illustrate this approach applied to an engineeringthermodynamics course. Our purpose here is to cause engineering educators to reflect on theircourse design to enhance the development of conceptual knowledge and not to force others toadopt our particular treatment of any subject. We illustrate how the richness of the subject canbe developed from a few key concepts and how such an approach can be useful in thescaffolding and transfer of knowledge to courses requiring such prerequisite knowledge. Wealso explore the application of other ideas from educational psychology to the teaching ofthermodynamics.References1. Chi, M. T. H., Glaser, R., Reese, E., ”Expertise in Problem Solving,” in Sternberg (Ed.), Advances in the Psychology of Human Intelligence, Vol. 1, Erlbaum, Hillsdale, NJ, 1982, pp. 7-75.2. Larkin, J., McDermott, J., Simon, D. P., and Simon, H. A., “Expert and Novice Performance in Solving Physics Problems,” Science 108: 1335-1342 (1980).3. Froyd, J. E., and Ohland, M. W., “Integrated Engineering Curricula,” Journal of Engineering Education, 147-164, January 2005.4. Richards, D. E., “Integrating the Mechanical Engineering Core,” Proceedings of the 2001 ASEE Annual Conference and Exhibition, 2001.

Stephen R. Turns, professor of mechanical engineering, joined the faculty of The Pennsylvania State University in 1979. His research interests include combustion-generated air pollution, other combustionrelated topics, and engineering education pedagogy. He is the author of three student-centered textbooks in combustion and thermal-sciences. He is a Fellow of the ASME and was the recipient of ASEE’s Mechanical Engineering Division Ralph Coats Roe Award in 2009.

BackgroundEven as expectations for engineers continue to evolve to meet global challenges, analytical problem solving remains a central skill. Thus, improving students' analytical problem solving skills remains an important goal in engineering education. This study involves observation of students as they execute the initial steps of an engineering problem solving process in statics.Purpose (Hypothesis)(1) What knowledge elements do statics students have the greatest difficulty applying during problem solving? (2) Are there differences in the knowledge elements that are accurately applied by strong and weak statics students? (3) Are there differences in the cognitive and metacognitive strategies used by strong and weak statics students during analysis?Design/MethodThese questions were addressed using think‐aloud sessions during which students solved typical textbook problems. We selected the work of twelve students for detailed analysis, six weak and six strong problem solvers, using an extreme groups split based on scores on the think‐aloud problems and a course exam score. The think‐aloud data from the two sets of students were analyzed to identify common technical errors and also major differences in the problem solving processes.ConclusionsWe found that the weak, and most of the strong problem solvers relied heavily on memory to decide what reactions were present at a given connection, and few of the students could reason physically about what reactions should be present. Furthermore, the cognitive analysis of the students' problems solving processes revealed substantial differences in the use of self‐explanation by weak and strong students.

Although many instructors may see the benefits of active and collaborative learning strategies, they may be reluctant to use them in their classes because they lack information on how to apply such strategies to specific mechanical engineering subjects. Here we present twenty-three in-class exercises that are useful for instruction in a first course in fluid mechanics. These exercises range from activities that consume a large portion of a class period to those that require just a few minutes, or less. Survey results show that our students are highly receptive to these exercises, welcoming them over a traditional lecture format. We also show that these exercises can he adapted readily by others and present limited evidence illustrating their effectiveness in improving student learning.

Preface Part I. Fundamentals: 1. Beginnings 2 Thermodynamic properties, property relationships and processes 3. Conservation of mass 4. Energy and energy transfer 5. Conservation of energy 6. Conservation of momentum 7. Second law of thermodynamics and some of its consequences 8. Similitude and dimensionless parameters Part II. Beyond the Fundamentals 9. External flows: friction, drag and heat transfer 10. Internal flows: friction, pressure drop and heat transfer 11. Thermal-fluid analysis of steady-flow devices 12. Systems for power production, propulsion, heating and cooling Appendix A. Timeline Appendix B. Thermodynamic properties of ideal gases and carbon Appendix C. Thermodynamic and thermo-physical properties of air Appendix D. Thermodynamic properties of H20 Appendix E. Various thermodynamic data Appendix F. Thermo-physical properties of selected gases at 1 ATM Appendix G. Thermo-physical properties of selected liquids Appendix H. Thermo-physical properties of hydrocarbon fuels Appendix I. Thermo-physical properties of selected solids Appendix J. Radiation properties of selected materials and substances Appendix K. Mach number relationships for compressible flow Answers to selected problems Index.

Fully revised to match the more traditional sequence of course materials, this full-color second edition presents the basic principles and methods of thermodynamics using a clear and engaging style and a wealth of end-of-chapter problems. It includes five new chapters on topics such as mixtures, psychrometry, chemical equilibrium, and combustion, and discussion of the Second Law of Thermodynamics has been expanded and divided into two chapters, allowing instructors to introduce the topic using either the cycle analysis in Chapter 6 or the definition of entropy in Chapter 7. Online ancillaries including a password-protected solutions manual, figures in electronic format, prepared PowerPoint lecture slides, and instructional videos are available.

Measurements of global emissions, flame radiation and flame dimensions are presented for unconfined turbulent-jet and precessing-jet diffusion flames. Precessing jet flames are characterised by increases in global flame radiation and global flame residence time for methane and propane fuels, however a strong dependency of the NOx emission indices on the fuel type exists. The fuel type dependence is considered to be because soot radiation is more effective than gas-radiation at reducing global flame temperatures relative to adiabatic flame temperatures and reducing the NO production rate.

Experimental studies and models of NOx formation in simple nonpremixed flames at atmospheric pressure are reviewed. Laminar flames are briefly discussed, while the bulk of the review focuses on axisymmetric, turbulent, jet flames. The issue of the scaling of NOx emission indices with nozzle exit diameter, initial jet velocity, and fuel type is a major theme of the article. The failure of a simple leading-order scaling is investigated and interpreted in terms of the various interrelated parameters affecting NO formation: the relative importance of various NO-forming chemical pathways, departures of O-atom concentrations and temperatures from their equilibrium values, flame strain, and flame radiation.

Experimental studies and models of NOx formation in simple nonpremixed flames at atmospheric pressure are reviewed. Laminar flames are briefly discussed, while the bulk of the review focuses on axisymmetric, turbulent, jet flames. The issue of the scaling of NOx emission indices with nozzle exit diameter, initial jet velocity, and fuel type is a major theme of the article. The failure of a simple leading-order scaling is investigated and interpreted in terms of the various interrelated parameters affecting NO formation: the relative importance of various NO-forming chemical pathways, departures of O-atom concentrations and temperatures from their equilibrium values, flame strain, and flame radiation.

Chemical and physical processes within aeolian sediments result in a reduction of the particle grain size. In loess sediments the post-depositional grain size variation is due to a reduction of the dominating coarse silt fraction in favor of the clay and fine silt fraction. Generally, there are two post-depositional fractionation processes: (1) the chemical weathering of silt sized minerals like mica and feldspar as a result of hydration and hydrolysis, (2) the physical weathering of all minerals contained in the primary loess sample by cryogenic and fluvial relocation processes. There are many widely used proxies to estimate their vertical variation in thick sediment columns. However, there are complicating factors related to aeolian sorting effects, the distance to the source regions and carbonate dynamics, which reduces the sensitivity of common proxies to the chemical weathering. In this study, we present a simple and quick method using laser diffraction calculations of grain size distribution obtained by two optical models (the Fraunhofer approximation and the Lorenz-Mie theory) to highlight the enrichment of fine grained material by post-depositional chemical weathering processes. In contrast to the Fraunhofer approximation, the Lorenz-Mie theory considers the complex refractive index which depends on the mineral properties. Thus, the difference of the grain size distributions (ΔGSD) calculated with both models is sensitive to the mineral composition of the sample. In separated submicron mineral suspensions we found that different crystalline properties are reflected by repeatable signatures of the ΔGSD. This specific ΔGSD-signature also occurs in the submicron grain size range of bulk measurements of weathered loess samples. In contrast to previous studies, we obtain reliable laser diffraction results in the submicron range. Summarizing, we present the ΔGSD within the submicron range of bulk measurements as a suitable indicator for the chemical weathering degree of loess-paleosol sequences, which is virtually unaffected by cryogenic processes, weak relocation of inherited weathering products and synsedimentary processes (sheet wash, saltation or enhanced background sedimentation).

Measurements of oxides of nitrogen and carbon monoxide emission indices, flame radiant fractions, and visual flame dimensions were made for turbulent jet diffusion flames covering a wide range of test conditions. Parameters investigated included: initial jet velocity, jet diameter, fuel type, fuel dilution with inerts, partial premixing with air, and location and quantity of radial air injection. Detailed temperature measurements were also obtained for selected test conditions. The objectives of the study were, first, to develop a well-characterized data base to guide modeling efforts, and second, to understand the relationships among NOx and CO emissions and flow conditions, fuel variables, and flame radiation. A major finding of the study was that the effects on NOx of residence time, flame temperature, and departure of the radical pool from equilibrium, whether caused by variations in initial jet velocity, jet diameter, fuel type, fuel dilution, or partial premixing, were well-characterized using two parameters: a characteristic nonadiabatic flame temperature, and a global residence time. Additional fuel-type dependencies, relating to the relative importance of prompt NO, were also found.