Support for instructional scaffolding with 1H NMR spectral features in organic chemistry textbook problems

Nuclear magnetic resonance (NMR) spectroscopy is vital to synthesis and provides rich problem-solving opportunities to organic chemistry students. Using the theories of scaffolding, interleaving, and blocking, our research systematically explores how textbooks introduce and reinforce spectral features when teaching students to solve 1H NMR spectroscopy problems. Specifically, we investigated the 1H NMR spectral features presented in worked examples and practice problems across four undergraduate organic chemistry textbooks. We examined the frequency and ordering of spectral features to explore how the textbooks could support scaffolded instruction. Spectral features like the number of signals and chemical shift were covered by problems more frequently, while integration was covered least. Our findings suggest that textbooks do not provide sufficient practice with all 1H NMR spectral features. We observed no discernible pattern in how textbooks ordered spectral features of 1H NMR in problems, indicating that there is little systematic method to the design of textbook chapters. Implications for textbook authors and editors, instruction, and research are discussed.

[1]  Vicente Talanquer,et al.  Classifying End-of-Chapter Questions and Problems for Selected General Chemistry Textbooks Used in the United States , 2010 .

[2]  Lisa K. Kendhammer,et al.  NMR Spectra through the Eyes of a Student: Eye Tracking Applied to NMR Items , 2017 .

[4]  Neil Mercer,et al.  'Scaffolding': learning in the classroom , 1992 .

[5]  M. Volman,et al.  Scaffolding in Teacher–Student Interaction: A Decade of Research , 2010 .

[6]  Philip N Chase,et al.  The effects of cumulative practice on mathematics problem solving. , 2002, Journal of applied behavior analysis.

[7]  F. Cotton,et al.  Basic Inorganic Chemistry , 1976 .

[8]  Ginger V. Shultz,et al.  Constraints on organic chemistry students’ reasoning during IR and 1H NMR spectral interpretation , 2019, Chemistry Education Research and Practice.

[9]  Bret J. Benesh,et al.  Undergraduate Students' Self-Reported Use of Mathematics Textbooks , 2012 .

[10]  James M. Nyachwaya,et al.  Features of Representations in General Chemistry Textbooks: A Peek through the Lens of the Cognitive Load Theory. , 2016 .

[11]  Jaan Mikk,et al.  Textbook: Research and Writing , 2000 .

[12]  Roy D. Pea,et al.  The Social and Technological Dimensions of Scaffolding and Related Theoretical Concepts for Learning, Education, and Human Activity , 2004, The Journal of the Learning Sciences.

[13]  George M. Bodner,et al.  Using students' representations constructed during problem solving to infer conceptual understanding , 2012 .

[14]  R. Kozma,et al.  Multimedia and understanding: Expert and novice responses to different representations of chemical phenomena , 1997 .

[15]  B. Rosenshine,et al.  The Use of Scaffolds for Teaching Higher-Level Cognitive Strategies. , 1992 .

[16]  Nathan McNeill,et al.  Indispensable Resource? A Phenomenological Study of Textbook Use in Engineering Problem Solving , 2013 .

[17]  J. Bruner From communication to language—a psychological perspective , 1975, Cognition.

[18]  F. Paas Training strategies for attaining transfer of problem-solving skill in statistics: A cognitive-load approach. , 1992 .

[19]  N. Mercer,et al.  Dialogue and the Development of Children's Thinking: A Sociocultural Approach , 2007 .

[20]  D. Rohrer,et al.  The benefit of interleaved mathematics practice is not limited to superficially similar kinds of problems , 2014, Psychonomic bulletin & review.

[21]  Y. Hsu,et al.  A REVIEW OF EMPIRICAL EVIDENCE ON SCAFFOLDING FOR SCIENCE EDUCATION , 2012 .

[22]  S. Engel Thought and Language , 1964 .

[23]  Vilma Mesa,et al.  Textbook mediation of teaching: an example from tertiary mathematics instructors , 2012 .

[24]  F. Paas,et al.  Variability of Worked Examples and Transfer of Geometrical Problem-Solving Skills: A Cognitive-Load Approach , 1994 .

[25]  J. Bruner,et al.  The role of tutoring in problem solving. , 1976, Journal of child psychology and psychiatry, and allied disciplines.

[26]  Doug Rohrer,et al.  The shuffling of mathematics problems improves learning , 2007 .

[27]  Eugene L. Chiappetta,et al.  A method to quantify major themes of scientific literacy in science textbooks , 1991 .

[28]  Nicholas C. Thomas,et al.  The early history of spectroscopy , 1991 .

[29]  Bruce Allen Knight,et al.  Teachers’ use of textbooks in the digital age , 2015 .

[30]  Vasiliki Gkitzia,et al.  Development and application of suitable criteria for the evaluation of chemical representations in school textbooks , 2011 .

[31]  J. Sweller,et al.  Effects of schema acquisition and rule automation on mathematical problem-solving transfer. , 1987 .

[32]  F. Paas,et al.  Measurement of Cognitive Load in Instructional Research , 1994, Perceptual and motor skills.

[33]  George M. Bodner,et al.  Mental Models : The Role of Representations in Problem Solving in Chemistry PROCEEDINGS , 2002 .

[34]  S. Puntambekar,et al.  Tools for Scaffolding Students in a Complex Learning Environment: What Have We Gained and What Have We Missed? , 2005 .

[35]  Slava Kalyuga,et al.  When problem solving is superior to studying worked examples. , 2001 .

[36]  Doug Rohrer,et al.  Interleaving Helps Students Distinguish among Similar Concepts , 2012 .

[37]  Mary Koppal,et al.  Meeting the challenge of science literacy: project 2061 efforts to improve science education. , 2004, Cell biology education.

[38]  F. Paas,et al.  Cognitive load theory and aging: effects of worked examples on training efficiency , 2002 .

[39]  L. Vygotsky Mind in Society: The Development of Higher Psychological Processes: Harvard University Press , 1978 .

[40]  Rosária Justi,et al.  Modelling, teachers' views on the nature of modelling, and implications for the education of modellers , 2002 .

[41]  R. Bjork,et al.  Learning Concepts and Categories , 2008, Psychological science.

[42]  Christopher N. Wahlheim,et al.  Spacing enhances the learning of natural concepts: an investigation of mechanisms, metacognition, and aging , 2011, Memory & cognition.

[43]  Jeffrey R. Raker,et al.  A Historical Analysis of the Curriculum of Organic Chemistry Using ACS Exams as Artifacts , 2013 .

[44]  George M. Bodner,et al.  Non-mathematical problem solving in organic chemistry , 2009 .

[45]  Ryan L. Stowe,et al.  Arguing from Spectroscopic Evidence , 2019, Journal of Chemical Education.

[46]  S. P. Parker Spectroscopy source book , 1988 .

[47]  Haley A. Vlach,et al.  The spacing effect in children’s memory and category induction , 2008, Cognition.

[48]  G. Shultz,et al.  Teaching assistants' topic-specific pedagogical content knowledge in 1H NMR spectroscopy , 2018 .

[49]  Joseph Krajcik,et al.  Supporting Students' Construction of Scientific Explanations by Fading Scaffolds in Instructional Materials , 2006 .

[50]  Melanie M. Cooper,et al.  Organic Chemistry, Life, the Universe and Everything (OCLUE): A Transformed Organic Chemistry Curriculum , 2019, Journal of Chemical Education.