Phys-MAPS: a programmatic physiology assessment for introductory and advanced undergraduates.

We describe the development of a new, freely available, online, programmatic-level assessment tool, Measuring Achievement and Progress in Science in Physiology, or Phys-MAPS ( http://cperl.lassp.cornell.edu/bio-maps ). Aligned with the conceptual frameworks of Core Principles of Physiology, and Vision and Change Core Concepts, Phys-MAPS can be used to evaluate student learning of core physiology concepts at multiple time points in an undergraduate physiology program, providing a valuable longitudinal tool to gain insight into student thinking and aid in the data-driven reform of physiology curricula. Phys-MAPS questions have a modified multiple true/false design and were developed using an iterative process, including student interviews and physiology expert review to verify scientific accuracy, appropriateness for physiology majors, and clarity. The final version of Phys-MAPS was tested with 2,600 students across 13 universities, has evidence of reliability, and has no significant statement biases. Over 90% of the physiology experts surveyed agreed that each Phys-MAPS statement was scientifically accurate and relevant to a physiology major. When testing each statement for bias, differential item functioning analysis demonstrated only a small effect size (<0.008) of any tested demographic variable. Regarding student performance, Phys-MAPS can also distinguish between lower and upper division students, both across different institutions (average overall scores increase with each level of class standing; two-way ANOVA, P < 0.001) and within each of three sample institutions (each ANOVA, P ≤ 0.001). Furthermore, at the level of individual concepts, only evolution and homeostasis do not demonstrate the typical increase across class standing, suggesting these concepts likely present consistent conceptual challenges for physiology students.

[1]  Alison J Crowe,et al.  GenBio-MAPS: A Programmatic Assessment to Measure Student Understanding of Vision and Change Core Concepts across General Biology Programs , 2019, CBE life sciences education.

[2]  Alison J Crowe,et al.  Tools for Change: Measuring Student Conceptual Understanding Across Undergraduate Biology Programs Using Bio-MAPS Assessments , 2019, Journal of microbiology & biology education.

[3]  Jo Van Hoey Using the , 2019, Beginning x64 Assembly Programming.

[4]  B. Couch,et al.  Multiple–True–False Questions Reveal the Limits of the Multiple–Choice Format for Detecting Students with Incomplete Understandings , 2018 .

[5]  Alison J Crowe,et al.  EcoEvo-MAPS: An Ecology and Evolution Assessment for Introductory through Advanced Undergraduates , 2018, CBE life sciences education.

[6]  Valerie S VanRyn,et al.  Physiology undergraduate degree requirements in the U.S. , 2017, Advances in physiology education.

[7]  Christian D. Schunn,et al.  The increasingly important role of science competency beliefs for science learning in girls , 2017 .

[8]  Patrícia Martinková,et al.  Checking Equity: Why Differential Item Functioning Analysis Should Be a Routine Part of Developing Conceptual Assessments , 2017, CBE life sciences education.

[9]  Anna Jo Auerbach,et al.  Curriculum Alignment with Vision and Change Improves Student Scientific Literacy , 2017, CBE life sciences education.

[10]  Macy A. Potts,et al.  How Question Types Reveal Student Thinking: An Experimental Comparison of Multiple-True-False and Free-Response Formats , 2017, CBE life sciences education.

[11]  Jenny McFarland,et al.  Validating a conceptual framework for the core concept of "cell-cell communication". , 2017, Advances in physiology education.

[12]  Jenny McFarland,et al.  The Core Concepts of Physiology , 2017 .

[13]  J. Michael,et al.  Development and Validation of the Homeostasis Concept Inventory , 2017, CBE life sciences education.

[14]  S. Mamede,et al.  First-year medical students' naïve beliefs about respiratory physiology. , 2016, Advances in physiology education.

[15]  J. McLaughlin,et al.  Vision & Change: Why it Matters , 2016, The American Biology Teacher.

[16]  J. Michael,et al.  A conceptual framework for homeostasis: development and validation. , 2016, Advances in physiology education.

[17]  J. Michael,et al.  A physiologist's view of homeostasis. , 2015, Advances in physiology education.

[18]  Brian A Couch,et al.  A Comparison of Two Low-Stakes Methods for Administering a Program-Level Biology Concept Assessment , 2015, Journal of microbiology & biology education.

[19]  Brian A. Couch,et al.  The Molecular Biology Capstone Assessment: A Concept Assessment for Upper-Division Molecular Biology Students , 2015, CBE life sciences education.

[20]  Mary Pat Wenderoth,et al.  Gender Gaps in Achievement and Participation in Multiple Introductory Biology Classrooms , 2014, CBE life sciences education.

[21]  Steven J. Pollock,et al.  Coupled multiple-response versus free-response conceptual assessment: An example from upper-division physics , 2014, 1407.6310.

[22]  Scott Freeman,et al.  BioCore Guide: A Tool for Interpreting the Core Concepts of Vision and Change for Biology Majors , 2014, CBE life sciences education.

[23]  Joel K. Abraham,et al.  The Genetic Drift Inventory: A Tool for Measuring What Advanced Undergraduates Have Mastered about Genetic Drift , 2014, CBE life sciences education.

[24]  J. Steedle Motivation Filtering on a Multi-Institution Assessment of General College Outcomes , 2014 .

[25]  Rebecca M. Price,et al.  The EvoDevoCI: A Concept Inventory for Gauging Students’ Understanding of Evolutionary Developmental Biology , 2013, CBE life sciences education.

[26]  Ngss Lead States Next generation science standards : for states, by states , 2013 .

[27]  Kathrin F. Stanger-Hall,et al.  Multiple-Choice Exams: An Obstacle for Higher-Level Thinking in Introductory Science Classes , 2012, CBE life sciences education.

[28]  R. Philip Chalmers,et al.  mirt: A Multidimensional Item Response Theory Package for the R Environment , 2012 .

[29]  Jennifer K Knight,et al.  Using the Genetics Concept Assessment to Document Persistent Conceptual Difficulties in Undergraduate Genetics Courses , 2012, Genetics.

[30]  Wendy K. Adams,et al.  Development and Validation of Instruments to Measure Learning of Expert‐Like Thinking , 2011 .

[31]  J. Michael,et al.  The core principles (big ideas) of physiology: results of faculty surveys , 2011, Advances in physiology education.

[32]  Quentin Vicens,et al.  A Diagnostic Assessment for Introductory Molecular and Cell Biology , 2010, CBE life sciences education.

[33]  R. Ranvaud,et al.  What is transmitted in "synaptic transmission"? , 2010, Advances in physiology education.

[34]  Jennifer K. Knight,et al.  Biology concept assessment tools: design and use , 2010 .

[35]  B. Panijpan,et al.  Hand-held model of a sarcomere to illustrate the sliding filament mechanism in muscle contraction. , 2009, Advances in physiology education.

[36]  Michael F. Middaugh Planning and Assessment in Higher Education: Demonstrating Institutional Effectiveness , 2009 .

[37]  Donna L. Sundre,et al.  Motivation Matters: Using the Student Opinion Scale to Make Valid Inferences About Student Performance , 2009, The Journal of General Education.

[38]  Jennifer K Knight,et al.  The Genetics Concept Assessment: a new concept inventory for gauging student understanding of genetics. , 2008, CBE life sciences education.

[39]  Ross H. Nehm,et al.  Measuring knowledge of natural selection: A comparison of the CINS, an open‐response instrument, and an oral interview , 2008 .

[40]  Charlene D'Avanzo,et al.  Biology Concept Inventories: Overview, Status, and Next Steps , 2008 .

[41]  Stella Vosniadou,et al.  Bridging culture with cognition: a commentary on “culturing conceptions: from first principles” , 2008 .

[42]  Klaus D. Kubinger,et al.  Item Difficulty of Multiple Choice Tests Dependant on Different Item Response Formats - an Experiment in Fundamental Research on Psychological Assessment , 2007 .

[43]  R. Nehm,et al.  Biology Majors' Knowledge and Misconceptions of Natural Selection , 2007 .

[44]  Joel Michael,et al.  What makes physiology hard for students to learn? Results of a faculty survey. , 2007, Advances in physiology education.

[45]  John E. Merrill,et al.  Assessing students' ability to trace matter in dynamic systems in cell biology. , 2006, CBE life sciences education.

[46]  W. Cliff Case study analysis and the remediation of misconceptions about respiratory physiology. , 2006, Advances in physiology education.

[47]  Mildred A. Hoover,et al.  Prevalence of blood circulation misconceptions among prospective elementary teachers. , 2005, Advances in physiology education.

[48]  G. Norman,et al.  Development and Evaluation of the Conceptual Inventory of Natural Selection , 2002 .

[49]  William Cliff,et al.  Undergraduates' understanding of cardiovascular phenomena. , 2002, Advances in physiology education.

[50]  Mark J. Gierl,et al.  Evaluating Type I Error and Power Rates Using an Effect Size Measure With the Logistic Regression Procedure for DIF Detection , 2001 .

[51]  Benjamin S. Bloom,et al.  A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom's Taxonomy of Educational Objectives , 2000 .

[52]  J A Michael,et al.  Undergraduate students' misconceptions about respiratory physiology. , 1999, The American journal of physiology.

[53]  Mark D. Reckase,et al.  Item Response Theory: Parameter Estimation Techniques , 1998 .

[54]  A. Odom,et al.  Development and application of a two‐tier diagnostic test measuring college biology students' understanding of diffusion and osmosis after a course of instruction , 1995 .

[55]  J. Mckillip,et al.  Fundamentals of item response theory , 1993 .

[56]  D. Frisbie,et al.  THE RELATIVE MERITS OF MULTIPLE TRUE‐FALSE ACHIEVEMENT TESTS , 1982 .