| Literature DB >> 21123699 |
David Coil1, Mary Pat Wenderoth, Matthew Cunningham, Clarissa Dirks.
Abstract
Most scientific endeavors require science process skills such as data interpretation, problem solving, experimental design, scientific writing, oral communication, collaborative work, and critical analysis of primary literature. These are the fundamental skills upon which the conceptual framework of scientific expertise is built. Unfortunately, most college science departments lack a formalized curriculum for teaching undergraduates science process skills. However, evidence strongly suggests that explicitly teaching undergraduates skills early in their education may enhance their understanding of science content. Our research reveals that faculty overwhelming support teaching undergraduates science process skills but typically do not spend enough time teaching skills due to the perceived need to cover content. To encourage faculty to address this issue, we provide our pedagogical philosophies, methods, and materials for teaching science process skills to freshman pursuing life science majors. We build upon previous work, showing student learning gains in both reading primary literature and scientific writing, and share student perspectives about a course where teaching the process of science, not content, was the focus. We recommend a wider implementation of courses that teach undergraduates science process skills early in their studies with the goals of improving student success and retention in the sciences and enhancing general science literacy.Entities:
Mesh:
Year: 2010 PMID: 21123699 PMCID: PMC2995770 DOI: 10.1187/cbe.10-01-0005
Source DB: PubMed Journal: CBE Life Sci Educ ISSN: 1931-7913 Impact factor: 3.325
Faculty ranking
| Science process skills | Average score of importance |
|---|---|
| Problem solving/critical thinking | 4.9 |
| Interpreting data: graphs and tables | 4.9 |
| Interpreting data: ability to construct an argument from data | 4.8 |
| Creating the appropriate graph from data | 4.7 |
| Communicating results: written | 4.7 |
| Ability to create a testable hypothesis | 4.7 |
| Ability to design an experiment: identifying and controlling variables | 4.6 |
| Ability to design an experiment: development of proper controls | 4.6 |
| Communicating results: oral | 4.6 |
| Knowing when to ask for guidance | 4.6 |
| Conducting an effective literature search | 4.6 |
| Reading and evaluating primary literature | 4.5 |
| Ability to design an experiment: proper alignment of experiment and hypothesis | 4.5 |
| Understanding basic statistics | 4.5 |
| Working independently when needed | 4.5 |
| Working collaboratively to accomplish a task | 4.4 |
| Being able to infer plausible reasons for failed experiments | 4.4 |
| Being able to effectively monitor their own learning progress | 4.3 |
| Creating a bibliography and proper citation of references | 4.2 |
| Interpreting data: gels, blots, microarrays, etc. | 4 |
| Being an effective peer mentor | 3.6 |
| Ability to use basic online bioinformatics tools (NCBI databases, BLAST, etc.) | 3.5 |
The average score of importance was determined by converting a descriptive Likert scale to a numerical scale (5 = Very Important, 4 = Important, 3 = Moderately Important, 2 = Of Little Importance, 1 = Unimportant), and taking the average.
Figure 1.The three skills selected by faculty (N = 156) as the most important for students to acquire in an undergraduate education as determined by comparing all averages. The percent faculty at different institutions is reported for each skill.
Figure 2.The three skills selected by faculty (N = 156) as the least important for students to acquire in an undergraduate education as determined by comparing all averages. Percent faculty at (A) R-1, non-R1, and liberal arts institutions and (B) community college is reported for each skill.
Figure 3.Faculty offered other skills (N = 74) that students should have by the time they graduate. These skills generally fell into one of eight categories and are reported as percent of the total.
Figure 4.Percent faculty (N = 156) at different institutions who felt that the amount of time they spent teaching science process skills was NOT sufficient.
Figure 5.Percent time (mean ± SEM) faculty (N = 156) at different institutions reported teaching skills as opposed to content. Values not sharing the same letter are significantly different from each other as determined by a one-way ANOVA and post hoc Tukey test.
Figure 6.Percent faculty (N = 100) selecting reasons that prevent them from spending more time teaching science skills. Numbers sum to greater than 100% due to respondents choosing more than one response.
Syllabus for the two-quarter (20 wk) BFP
| Faculty instruction and student activities per 1.5-hour sessions | ||
|---|---|---|
| Faculty | Student | |
| Session 1 | Introductions | Scientific literature pretest |
| Finding a research experience - I | Primary literature | |
Science interests discussion | Overview of scientific literature papers Finding journal articles | |
| How people learn | Writing assignment 1 (pretest) | |
Study skills I – Bloom's taxonomy, learning styles, and metacognition Identifying your learning styles Creating time-management tables | Outline Experimental design | |
| Session 2 | Writing assignment 1 (pretest) collected | Study skills II |
| Scientific writing | ||
Structuring your writing - outlines Grading rubrics | Diagramming questions Answering short essay questions Collaborative learning | |
| Session 3 | Experimental design | Oral reports group A |
Basic experimental design – controls, variables, hypotheses, predictions, and sample size | Primary literature papers Science communication | |
| Session 4 | Graphing in the computer laboratory | Computer laboratory exercise |
| Writing assignment 2 | ||
Graphs I – types of graphs, reading graphs, graphs to text Data display and analysis Graphing in Excel | Outline Experimental design | |
| Session 5 | Writing assignment 2 collected | Oral reports group B |
| Finding a research experience - II | ||
Research opportunities Drafting a letter to potential mentors | Primary literature papers Science communication | |
| Session 6 | Basic Statistics | Oral reports group C |
Graphs II – practice exercises, error bars, and data presentation Statistics – | Primary literature papers Science communication | |
| Session 7 | Data Analysis | Writing assignment 3 |
Working with and graphing data sets Interpreting results – supporting or refuting your hypothesis | Outline Experimental design Graphing Basic statistics Data analysis Structure of a scientific paper | |
| Oral Reports Group D | ||
Primary literature papers Science communication | ||
| Session 8 | Writing assignment 3 collected | Oral Reports Group E |
| Practice activities | ||
Experimental design Data analysis | Primary literature papers Science communication | |
| Session 9 | Basic bioinformatics | Computer laboratory exercises |
National Center for Biotechnology Information databases and tools Protein structures and Cn3D software | Data analysis Science tools and communication | |
| Session 10 | Guest panel | Question and answer session |
Physicians, scientists, dentists, nurses, graduate students | Careers in science and medicine | |
| Session 11 | Science posters | Computer laboratory exercise |
Schematics in biology Components of scientific posters | Drawing in PowerPoint Data analysis | |
| Session 12 | Study skills III | Oral presentations group 1 |
Concept mapping | Primary literature papers Science communication | |
| Session 13 | Practice activities | Writing assignment 4 |
Experimental design Data analysis | Scientific writing Experimental design Graphing Data analysis | |
| Oral presentations group 2 | ||
Science communication Primary literature papers | ||
| Session 14 | Undergraduate research symposium | Undergraduate scientific poster sessions (Biology Fellows required to attend) Closing celebration |
Career booths Graduate school programs Biology Fellows program Undergraduate research opportunities | ||
| Session 15 | Writing Assignment 4 collected | Oral presentations group 3 |
| Practice activities | ||
Experimental design Data analysis | Primary literature papers Science communication | |
| Session 16 | Study skills IV | Writing assignment 5 (posttest) |
Collaborative learning - peer teaching | Scientific writing Experimental design | |
| Oral presentations group 4 | ||
Primary literature papers Science communication | ||
| Session 17 | Writing assignment 5 collected | Oral presentations group 6 |
| Study skills V | ||
Collaborative learning, group problem solving | Primary literature papers Science communication | |
| Session 18 | Careers in science | Student career interests |
Graduate and medical school topics Alternative science careers | Casting ahead Five and ten year plans | |
| Scientific literature posttest | ||
| Session 19 | Pathway planning | Academic and professional roadmaps |
Identifying components necessary for meeting career goals | Mapping out a plan to meet a professional goal | |
| Session 20 | Deconstructing the BFP | Student planning and social time |
Review of BFP learning objectives and program activities Planning ahead – supplemental instruction for introductory biology and BFP as a scholarly network | Students share their academic schedules Students form future study groups for subsequent science courses | |
Figure 7.A schematic representing the kinds and timing of class instruction and practice between assignments.
Figure 8.Percent of total points (mean ± SEM) received during either a pretest or a posttest on scientific writing (graded with the SWR; N = 44) or SLT (N = 42) for 2006 BFP students. Statistically significant differences by paired t-test are indicated in the figure.
Flowchart of BFP activities during supplemental instruction sessions
| Survey | Pretest | Survey | Practice activities | Survey | Posttest | Survey |
|---|---|---|---|---|---|---|
| 2 min | 30 min | 2 min | 50 min | 2 min | 30 min | 2 min |
| 10 short answer questions at 6 levels of Blooms | Content problems from multiple sources | 10 short answer questions at 6 levels of Blooms |
Figure 9.Students' understanding scores (mean ± SEM) for each of the topics (7–8 per module) were averaged to give the student one understanding score at each of the four time points for that module. Individual students completed between one and four modules. If students completed more than one module, their understanding scores were averaged across modules. Thus, each student (N = 39) received a composite score at each time point. Statistically significant differences by paired t-test are indicated in the figure.
Sample student quotes