Subject Index - ACS Publications

Subject Index A Areas of interest, 211

Downloaded by 203.64.11.45 on April 2, 2015 | http://pubs.acs.org Publication Date (Web): July 31, 2014 | doi: 10.1021/bk-2014-1166.ix002

B beSocratic, 227 activities, examples help students learn to develop arguments and explanations, 235 model to describe energy changes, 234 data analysis, 231 examples of using, 229f post-analysis research tools, 231 screenshot, 228f

C CER. See Chemistry education research (CER) Chemistry diagnostic assessments and concept inventories atomic emission and flame tests, 165 biochemistry (multiple concepts), 165 bonding, 165 chemical reactions/light/heat, 165 enzyme-substrate interactions, 166 equilibrium, 166 general chemistry (multiple concepts), 166 inorganic qualitative analysis, 166 ionization energy, 166 organic acid strength, 166 particulate nature of matter, 166 redox reactions, 166 structure of matter/changes of state/solubility/solutions, 166 Chemistry education research (CER), 1 Chemistry education research, eye tracking methodology basics of vision, 192 data analysis area of interest, 209 example textbook selection, areas of interest, 210f heatmaps, 213 scanpath analysis, 212 scanpath overlaid on stimulus, 212f

data collection, 207 experimental design, 202 eye tracking studies, sample size, 205t protocol and stimuli, 205 research questions, 203 sample population size, 204 study type, 203 eye movements and cognitive processes, relationship, 193 eye trackers, types configuration of hardware, 195 dark pupil versus bright pupil, 196 eye tracking versus gaze tracking, 194 monocular versus binocular tracking, 196 fixation and saccade definitions, 208t language of eye tracking, 193 types of research, 196 pupillometry, 200 reading, 197 scene perception, 198 usability, 197 visual search, 199 Concept mapping, 173

D Dealing with nonsignificant results chemistry education research, specific issues to be addressed, 244 planning and post-hoc analysis, two-pronged approach, 263 two-pronged approach, 246 Dedoose screen capture excerpt in interview transcript, 88f set of descriptors, 87f

E Examine teaching and learning in classroom classroom discourse analysis, 62 discourse analysis studies, methodological considerations additional sources of data, 71 audio and video recordings, 69 data analysis, transcription and its role, 71 data collection, 69

349 In Tools of Chemistry Education Research; Bunce, D., et al.; ACS Symposium Series; American Chemical Society: Washington, DC, 2014.


limitations, 75 reliability and validity, 74 unit of analysis, 73 discourse in CER contexts, analyzing approaches analyzing argumentation, alternate frameworks, 66 analyzing role of instructor, more frameworks, 68 argumentation in collaborative classrooms, 65 coordinating instructor discursive moves with argumentation, 67 inductive and deductive approaches, 64 Eye tracking advantages, 200 disadvantages, 201 limitations, 202

G Get started on your own research, 335 achievement on multiple choice questions, 338 choosing and handling incoming data, 340 collecting data, 337 IRB review, 340 lab effect on student understanding, 336 measure student’s understanding of chemistry, 338 problems, relevant application framework, 339 research question, type, 339 student understanding, multivariate methods, 337

H F Facilitate qualitative data analysis analyzing qualitative data annotating data, 90 assumptions and heuristics, characterization, 86 CAQDAS packages, 86 coded data, retrieval, 89 coding of data, 87 final considerations, 93 handling and organizing data, 85 other functionalities, 92 screen capture of code window in Dedoose, 90f visualizing data, 91 computer assisted qualitative data analysis (CAQDAS), 83 using qualitative analysis software, 83 Family Education Rights and Privileges Act (FERPA), 337 FERPA. See Family Education Rights and Privileges Act (FERPA) Fundamental statistics in SPSS and R basic inferential statistics difference and association, analysis, 143 nonparametric statistics, 145 regressions, 144 reliability analysis, 144 descriptive statistics, R command, 142t descriptive statistics and graphics, 142 inferential statistics, R commands, 143t

Human participants in chemistry education research, 279. See Writing application began need IRB review, 280 understand local review process, 282 ethical educational innovation, 294 levels of review continuing review and modifications, 292 exempt review, 291 expedited review, 291 full review, 292 projects involving multiple institutions, 293 review end, 294 nature and scale of risks examples, 286 experiments, 289 faculty participants, 289 incentives, 288 international studies, 290 levels of risk and possible risk management strategies, 287t minors, 290 writing application

I Interactive Multi-Media Excercises (IMMEX) software, 222 Investigating chemistry teaching and learning



analyzing observational data analyzing teaching and learning, observation protocols, 21 applying general qualitative procedures, 20 classroom observation protocols analyzed, common and varying characteristics, 23t discourse analysis, 21 observation protocols with particular promise for chemistry, 24 research-based observation protocols, 22t capturing observational data advantages of video, 18 audio and video, 17 chemistry classroom phenomena, 18 chemistry classrooms, special considerations, 20 field notes, 17 role of artifacts, 19 video tools, 19 videos’ multimodal record, 18 collecting observational data, planning consenting and non-consenting students, 16 design considerations, 14 human subjects and related logistical considerations, 14 K-12 schools, 15 observational versus self-report data, 13 observations of public behavior, 15 participant-observer continuum, 12 school districts, 15 observational research, reporting results, 26 validity and reliability considerations, 25

M Manuscript submission preparation manuscript should include abstract, 313 conclusion/discussion/implications, 317 data collection and analysis, 315 findings/results, 316 focus and overall coherence, 317 indicative title, 313 keywords, 314 methodology, 315 participants and research context, 315 previous literature, review, 314

research question, 314 target journal selection, 304 ensuring fit with journal, 307 evaluating journal as outlet, 311 journal quality, some indicators, 311t journal theme issues in CER, examples, 309t major journals in field, 305 publication models, 306 reaching professional audience, 310 specialist and interdisciplinary science education journals, 308 theme/special issues, 309 writing style, first or third person, 312 Measure students’ conceptual knowledge of chemistry chemistry education researchers, recommendations, 164 classroom teachers, recommendations, 164 content selection, 157 development methods, 156 eliciting students’ ideas, 158 exemplar assessment tools, 156 item design, 158 measuring chemistry learned, 162 two-tier questions, response patterns for students, 163t Multi-classroom collaborations calendar system, 269 making it work say with data, 276 turn constraints into affordances, 275 view mistakes as opportunities, 276 monitoring and controlling classroom observations, 273 data collection protocols, 273 regular contact with collaborators, 274 screen data, 272 planning, 268 attrition, 269 collaborators, ask questions, 271 expect confusing IRB rulings, 270 incorporate pilot studies, 270

N Nonparametric statistical tests comparison of groups Kruskal-Wallis test, 130 Mann-Whitney test, 129 conclusions and further readings, 132 example contingency table, 119t with expected values, 120t



citation of work, 328 do with work, 328 open-access archiving and article repositories, 328 peer review process editorial decisions, 323 editorial input into review, 323 manuscripts screening, 322 review decisions, responding, 324 reviewers selection, 322 revising manuscript, 325 submission process, 319 author center at journal website, 320 information, asked to provide, 321 need to upload, 320 saving images at two different resolutions, 320f

Kendall’s τ example data, 123t Kruskal-Wallis example, 131t logistic regression equation, predicted probabilities, 126f Mann-Whitney example, 129t measures of association chi-square (χ2) test, 119 Kendall’s tau (τ), 123 logistic regression, 124 Spearman’s rho (ρ), 121 output from logistic regression, 125t repeated measures Wilcoxon Signed Rank test, 127 Spearman’s ρ example data, 122t Wilcoxon Signed Rank test, sorted data, 128t Nonparametric statistics in chemistry education research data scales, 116 mapping nonparametric tests to parametric counterparts, 118t nonparametric versus parametric, 117

Q

O Open-ended interviews continuum of types, 34f semi-structured interviews, 36 structured interviews, 35 unstructured interviews, 34 OrganicPad, 225

P Planning for publishable research importance of research, 301 determining authorship, 303 informed consent, 302 no expectation of harm or disadvantage, 303 participants and institutions, anonymity, 303 research with human participants, ethical guidelines, 302 logical chain supporting research claims, 300 quality research, 304 Preparing chemistry education research manuscripts for publication after approval or acceptance, 325 citing and reproducing work assigning copyright or licensing work, 327

Qualitative network analysis, 183 after qualitative manipulation, visualization of GEPHI network, 184f chemistry education research, 185 proximity data, 185 state and organization collaboration networks, 185 state collaboration networks from different perspectives, 186f visualization of network in GEPHI, 184f Quantitative network analysis averaged expert referent pathfinder network, 181f coherency, 179 collecting proximity data, rating program, 181f neighborhood similarities, 180 path length correlation, 179 stoichiometry topic, student pathfinder network, 182f Questions better answered by R effect size, 145 permutation tests, 146 Rasch model, 146 summary, 148

R Reasons to learn and use advantages community-backed, 137 free and open-source, 136


powerful and flexible, 137 disadvantages, 138


S Single dependent variable independent measures one-way ANOVA, 104 two (or more)-way ANOVA, 106 repeated measures one factor repeated-measures ANOVA, examples, 110 repeated-measures versus independent-groups designs, 109 Submitted manuscript presentation, 317 acknowledgements, 318 appendices and supplementary materials, 318 blinded versions, 319 headings and sub-headings, 318 references, 319 use of tables and figures, 318

T Tools of chemistry education research analyzing quantitative research data, 3 application, 6 chemistry education research cognitive-based tools, 4 planning, conducting, and publishing, 5 qualitative research, strategies, 2 Tools to measure students’ mental organization of chemistry information. See Network analysis chemistry education research, 187 Lewis structure for NH4+, 170 network analysis structural knowledge, 171 concept mapping, 173 concept maps drawn by chemistry students, 174f creating structural network, proximity data, 178f elements, 172 evaluate concept maps, algorithm, 175 network representations, 172 networks, 177 portion of network representation of chemical bonding, 173f

proximity data collection methods, 176t proximity data techniques, 176 Two-pronged approach to dealing with nonsignificant results, 246 gaze patterns after hint, 260f before hint, 260f online HW study, questions and results, 255t planning asking good questions, 247 building in backup, 252 experimental design and theoretical framework, 247 modifying or creating tools, 251 multivariable design, 250 pilot vs preliminary studies, 253 revising the question, 249 theoretical framework, 247 triangulate data, 252 post-hoc analysis analysis of data, 257 double check data and statistical output files, 257 nonsignificant results validity, 262 revisit research question, 258 revisit theoretical framework, 261 summary of planning for nonsignificant results, 256

U Use of analysis of variance in chemistry education research, 99 ANOVA technique used, types, 103 assumptions about data, 102 difference determination method, 100 test statistics, 101 example of two-way mixed ANOVA, 111 mixed between and within designs, 111 multiple dependent variables, 112 one-way ANOVA, example, 105 sample ANOVA table, 105f summary, 112 three-way ANOVA, examples, 108 two-way ANOVA output, 107f Use of technology to model and analyze student data online and face-to-face courses, 220 systems allow data capture for later analysis



beSocratic, formative assessment system, 226 grid view of group of students’ submissions for question, 232f hidden Markov modeling, 233f Interactive Multi-Media Excercises (IMMEX), 221 moving from IMMEX to OrganicPad, 224 process for data collection and analysis using IMMEX, 223f science practices, development and assessment, 226 screenshots of feedback, 230f technology improves learning outcomes, 220 Using interviews in CER projects, 31. See Open-ended interviews analyzing interview data qualitative coding, 54 theoretical framework, importance, 53 transcription, 52 triangulation, 55 conducting interview developing rapport, 47 email interviews, 50 giving participants appropriate feedback and support, 48 media for, 49 other media for interviews, 51 paying attention, 47 phone interviews, 50 pros and cons, 51t recording interview data, 48 video chat, 51 developing interview protocol construct good interview questions, 41 identifying desired information before starting interview, 40 piloting interview protocol, 44 qualitative interviews questions, types, 42t

think-aloud protocols, construct good tasks, 43 focus group interviews, 38 interviews, types, 33 open-ended interviews selecting participants, 45 quantitative methods, 46 sampling methods, 46 structured open-ended and think-aloud interviews, 33t summary, 56 think-aloud interviews, 39 Using statistical program R getting help globally and locally, 140 importing data sets, 140 installation and interface, 138 output, 141 packages, 140 R console window, 139f R files, 141 screen shot of RStudio, 139f

V Validity and reliability of data limitations, 161 reliability methods, 161 validity methods, 159 Variance techniques, need for analysis, 103

W Writing application description, 285 electronic communication, 285 formats, 285


Subject Index - ACS Publications

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