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Dissertations / Theses on the topic 'Data Science Education'

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Published: 10 December 2022
Last updated: 29 January 2023

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1

DeVaney, Jonah E. "tidyTouch: An Interactive Visualization Tool for Data Science Education." Digital Commons @ East Tennessee State University, 2020. https://dc.etsu.edu/honors/529.

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Accessibility and usability of software define the programs used for both professional and academic activities. While many proprietary tools are easy to grasp, some challenges exist in using more technical resources, such as the statistical programming language R. The creative project tidyTouch is a web application designed to help educate any user in basic R data visualization and transformation using the popular ggplot2 and dplyr packages. Providing point-and-click interactivity to explore potential modifications of graphics for data presentation, the application uses an intuitive interface to make R more accessible to those without programming experience. This project is in a state of continual development and will expand to cover introductory data science topics relevant to academics and professionals alike. The code for tidyTouch and this document can be found at https://github.com/devaneyJE/tidyTouch_thesis (see ui.R and server.R files for application code).
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2

MacIntyre, Thomas Gunn. "Using and applying international survey data on mathematics and science education." Thesis, University of Edinburgh, 2014. http://hdl.handle.net/1842/10542.

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There were two purposes set out in this study, first to identify the principal associations with educational performance of Scottish students as reported in the 2007 wave of the Trends in International Mathematics and Science Study (TIMSS2007), and second to evaluate methods of data analysis where sample surveys use plausible value (PV) methodology. Four sets of data were used for the secondary analysis of TIMSS2007, with student's responses to cognitive items and questionnaire data emanating from two stages (G$ and G*) that each addressed two disciplines (mathematics and science). Explanatory models for each stage and discipline were analysed using hierarchical linear modelling techniques to accommodate the cluster sample design of the survey. Guided by existing literature in STEM education the study examined elements of students' learning experiences that fell within a social constructivist theory of learning to ascertain whether the empirical data supported current claims on effective practice. A number of control variables were included in the analyses, some well-established constructs and others derived from background questionnaires. Overall, the results showed that selected background characteristics were consistently related to mathematics and science achievement. The strength of association with home resources, and although girls were generally associated with lower achievement scores, that gender association was strongest in G4 mathematics achievement. The findings suggest there is limited support for current claims in respect of a reform agenda that privileges discussion and collaborative group work. Other policy initiatives on assessment for learning and using technologies in class are not supported in the data, with either no evidence of association or a significant negative effect in the models of mathematics and science achievement. Aspects of practical work and scientific enquiry are positively associated with G4 science achievement, with particular credence given to 'doing' and 'watching' experiments or investigations, buy there is no association with achievement scores at G8 for any of planning, watching or conducting experiments. This latter finding provides empirical evidence of difference across stages on an aspect of practice that is heavily debated. The primary method of analysis utilised a four-level structure, with PV as the unit of analysis. Substantive findings were compared with alternative methods: first making the dependent variable an average of the five PVs; second using one PV as the response variable; and third computing statistics from all five PVs and merging results using Rubin's Rules for combining multilevel method underestimates standard errors in the model in the same way as witnessed for the average of PVs. This leads to the conclusion that the only valid route to analysing imputed data is through Rubin's method of combining results from all five PVs.
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3

Anderson, Amie K. "Use of admissions data to predict student success in postsecondary freshman science." Thesis, Capella University, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3609412.

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The purpose of this study was to determine if significant relationships exist for any of the variables, age, gender, previous GPA, test scores (ACT, Compass), number of accumulated credits, and student success in Biology. This study strived to determine what academic/admissions data can be used to determine the likelihood of student success in Biology. A quantitative correlational study using stepwise multiple regression analysis was used for this study. The study was a retrospective study. Data was composed of a convenience archival sample from the institutional database. Multiple regression analysis was conducted to determine the effect each independent variable has on the dependent variable of student success. For the data set ACT, the variables math score, prealg score, writing score, reading score, and previous GPA were all significant. For data set CMP the variable of student's age was not significant, but the other variables were significant. For the Blanks data set, the only variable of significance was gender. Using stepwise multiple regression analysis the data sets produced regression models showing predictability based on stepwise significance. For Blanks data set, the variables previous hours earned, gender, age, and previous GPA were used. For the ACT data set, math score and reading score were used. For the CMP data set the variables included math score, writing score, previous GPA, gender, reading score, and previous hours earned. The level of predictability of the regression equation for the ACT data set and Blank data set was low. However, the predictability for the CMP data set was moderate. The highest percent of variance explained by the regression models was 11.6% of the CMP data set.

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4

Planteu, Lukas, Bernhard Standl, Wilfried Grossmann, and Erich Neuwirth. "Integrating school practice in Austrian teacher education." Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2013/6462/.

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We present a concept of better integration of practical teaching in student teacher education in Computer Science. As an introduction to the workshop different possible scenarios are discussed on the basis of examples. Afterwards workshop participants will have the opportunity to discuss the application of the aconcepts in other settings.
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5

Nylén, Aletta, and Christina Dörge. "Using competencies to structure scientific writing education." Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2013/6485/.

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Scientific writing is an important skill for computer science and computer engineering professionals. In this paper we present a writing concept across the curriculum program directed towards scientific writing. The program is built around a hierarchy of learning outcomes. The hierarchy is constructed through analyzing the learning outcomes in relation to competencies that are needed to fulfill them.
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6

Nadarajah, Kumaravel. "Computers in science teaching: a reality or dream; The role of computers in effective science education: a case of using a computer to teach colour mixing; Career oriented science education for the next millennium." Thesis, Rhodes University, 2000. http://hdl.handle.net/10962/d1003341.

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Science education in South Africa is not improving much. Many science educators do not have appropriate science qualifications. Majority of the learners have limited facilities to learn science. In this dilemma the move to OBE may result in further substantial deterioration of science education. A possible way out is to use computers in science education to facilitate the learning process. This study was designed to investigate how computers contribute to learners’ skills development in a physics course. A series of interactive computer simulations of colour mixing and a number of closely related traditional practical activities are aimed to promote learners’ understanding of colour. It was concluded that while computer environments have greater potentialas learning tools, they also limit interactions in significant ways.
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7

Keiler, Leslie Susan. "Factors affecting student data handling choices and behaviours in Key Stage 4 science." Thesis, University of Oxford, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.323549.

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8

Ng, Kevin (Kevin Y. ). "Design of a teacher education model that improves teacher educator efficiency in processing teacher candidate data." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/119729.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 49-50).
Existing state of the art practice-based teacher education models either rely on heavy teacher educator time commitment to process teacher candidate performance stored in rich media like audio or video, or rely on teacher candidates to voluntarily share experiences with minimal teacher educator interaction with data. Using an iterative design process, I work with teacher educators to gauge interest in and build a new teacher education model that simplifies how teacher educators interact with rich media. The new model builds on Teacher Moments, an online simulator for preservice teachers, and takes advantage of state of the art speech recognition and data visualization technology to help teacher educators learn the contents of rich media generated by teacher candidates without dedicating the time to listen or watch media. In my investigation, I find that there is an interest in such a model and that the new model succeeds in empowering teacher educators with the ability to use teacher candidate data to inform instructional decisions and substantiate discussion point during group debrief sessions.
by Kevin Ng.
M. Eng.
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9

Robertson, Laura, Mahua Chakraborty, and Pamela J. Cromie. "Thinking Like a Scientist: Data Analysis in Middle and High School." Digital Commons @ East Tennessee State University, 2012. https://dc.etsu.edu/etsu-works/779.

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10

LaMar, Michelle Marie. "Models for understanding student thinking using data from complex computerized science tasks." Thesis, University of California, Berkeley, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3686374.

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The Next Generation Science Standards (NGSS Lead States, 2013) define performance targets which will require assessment tasks that can integrate discipline knowledge and cross-cutting ideas with the practices of science. Complex computerized tasks will likely play a large role in assessing these standards, but many questions remain about how best to make use of such tasks within a psychometric framework (National Research Council, 2014). This dissertation explores the use of a more extensive cognitive modeling approach, driven by the extra information contained in action data collected while students interact with complex computerized tasks. Three separate papers are included. In Chapter 2, a mixture IRT model is presented that simultaneously classifies student understanding of a task while measuring student ability within their class. The model is based on differentially scoring the subtask action data from a complex performance. Simulation studies show that both class membership and class-specific ability can be reasonably estimated given sufficient numbers of items and response alternatives. The model is then applied to empirical data from a food-web task, providing some evidence of feasibility and validity. Chapter 3 explores the potential of using a more complex cognitive model for assessment purposes. Borrowing from the cognitive science domain, student decisions within a strategic task are modeled with a Markov decision process. Psychometric properties of the model are explored and simulation studies report on parameter recovery within the context of a simple strategy game. In Chapter 4 the Markov decision process (MDP) measurement model is then applied to an educational game to explore the practical benefits and difficulties of using such a model with real world data. Estimates from the MDP model are found to correlate more strongly with posttest results than a partial-credit IRT model based on outcome data alone.

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11

Gxwati, Ntombizandile Irene. "The education management information system of the Free State Department of Education : a systems analysis." Thesis, Stellenbosch : University of Stellenbosch, 2011. http://hdl.handle.net/10019.1/6487.

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Thesis (MPhil (Information Science))--University of Stellenbosch, 2011.
ENGLISH ABSTRACT: Organizations depend on the availability of reliable and credible information to make informed decisions and to plan effectively. The Education Management Information System (EMIS) is used by all provincial education departments including the Free State Department of Education for collecting, verifying, analysing, storing and disseminating reliable and credible data for decision making and planning purposes. Through its efforts to improve information management, the Department of Basic Education introduced the South African School Administration Management System (SA-SAMS) to improve the management of data at school level and allow for the uploading of this data onto provincial databases. This study focuses on an analysis of the Education Management Information System to determine whether this information system, utilised by the Free State Department of Education, is reliable and credible or not. In order to answer the research question under study, the dimensions/constructs of information systems success, such as information quality, system quality, individual and organizational impacts have been used to evaluate the information systems under investigation. Chapter 1 introduces the topic and outlines the background and the accountability chain of the Free State Department of Education. Chapter 2 deals with the theoretical grounding. It discusses the topic of Information Systems, in particular what the criteria used to determine the efficiency and reliability of an education management system in the Free State Province are. Chapter 3 draws on the theoretical base outlined in Chapter 2, focussing on the Free State Province to model the EMIS system and identifying the crucial elements where empirical observations are necessary. In Chapter 3 the focus is on the empirical data collection based on the model as set out in Chapter 4. In this chapter the methodological concerns in respect of the collection of data are dealt with in detail, and the findings are reported. In Chapter 4 the implications of the findings are weighed up against the criteria as identified in Chapter 2 and conclusions are drawn on that basis. Lastly Chapter 5, which draws on earlier findings, presents the lessons learnt in doing this research, conclusions drawn therefrom, as well as the recommendations presented as a way forward to improve the gaps identified in Free State EMIS. The researcher’s informed conclusion is that EMIS, through the use of SA-SAMS, has improved the capturing of data at school level and that this has contributed to an improvement in the quality of data contained in the provincial database.
AFRIKAANSE OPSOMMING: Organisasies is afhanklik van die beskikbaarheid van betroubare en geloofwaardige inligting ten einde ingeligte besluite te neem en effektief te beplan. Die Onderwysbestuursinligtingstelsel (EMIS) word deur al die provinsiale onderwysdepartemente gebruik, insluitend die Vrystaatse Onderwysdepartement, vir die versameling, verifiëring, analise, berging en disseminasie van betroubare en geloofwaardige data vir die doeleindes van besluitneming en beplanning. Deur sy pogings om inligtingbestuur te verbeter, het die Departement van Basiese Onderwys die Suid-Afrikaanse Skoolbestuurstelsel (SA-SAMS) ingestel om die bestuur van data op skoolvlak te verbeter en om voorsiening te maak vir die oordrag van hierdie data na provinsiale databasisse. Hierdie studie fokus op ‘n analise van die Onderwysbestuursinligtingstelsel om vas te stel of hierdie stelsel, wat deur die Vrystaatse Onderwysdepartement gebruik word, betroubaar en geloofwaardig is, al dan nie. Ten einde die navorsingsvraag van hierdie studie te beantwoord, is die dimensies/konstrukte van die sukses van inligtingstelsels, soos inligtingskwaliteit, stelselkwaliteit, individuele en organisatoriese impak, gebruik om die betrokke inligtingstelsels te evalueer. Hoofstuk 1 lei die onderwerp in en verstrek die agtergrond en aanspreeklikheidsketting van die Vrystaatse Onderwysdepartement. Hoofstuk 2 behandel die teoretiese begronding. Die onderwerp Inligtingstelsels word bespreek, veral die kriteria wat gebruik word om die doeltreffendheid en betroubaarheid van ‘n onderwysbestuurstelsel in die Vrystaatse Provinsie te bepaal. Met die teoretiese basis wat in Hoofstuk 2 uiteengesit is as vertrekpunt, fokus Hoofstuk 3 op die Vrystaatse Provinsie om die EMIS te modelleer en om die deurslaggewende elemente waar empiriese waarnemings nodig is, te identifiseer. In Hoofstuk 3 is die fokus op die versameling van empiriese data, gebaseer op die model wat in Hoofstuk 4 beskryf word. In hierdie hoofstuk word die metodologiese vraagstukke met betrekking tot die versameling van data in besonderhede behandel, en die bevindings word aangebied. In Hoofstuk 4 word die implikasies van die bevindings gestel teenoor die kriteria wat in Hoofstuk 2 geïdentifiseer is, en gevolgtrekkings word gemaak. Laastens word in Hoofstuk 5, gebaseer op vroeëre bevindings, die lesse wat uit hierdie navorsing geleer is, aangebied, gevolgtrekkings word gemaak, en aanbevelings word voorgehou as die pad vorentoe om leemtes wat in die Vrystaatse EMIS geïdentifiseer is, te verbeter. Dit is die navorser se ingeligte gevolgtrekking dat EMIS, deur die gebruik van SASAMS, die vaslegging van data op skoolvlak verbeter het, en dat dit bygedra het tot ’n verbetering van die kwaliteit van data in die provinsiale databasis.
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12

Sickel, Jamie L. "TPACK Development in Science Teacher Preparation: A Case Study in Queensland, Australia." Ohio University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1457379586.

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13

Baker-Lawrence, Anika Rae. "An Investigation into Instructional Support for Data Analysis in High School Science Inquiry." PDXScholar, 2013. https://pdxscholar.library.pdx.edu/open_access_etds/1534.

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The implementation of scientific inquiry in the high school classroom has proven to be not only relevant and exploratory, but challenging and engaging as well. This style of curriculum design has been recognized as a primary means of achieving the goals and objectives set by the National Resource Council (NRC, 1996). While much research has shown that science inquiry helps students to gain understanding of content knowledge, little research has been conducted to assess gains in higher order thinking skills, specifically those related to data analysis (Anderson, 2002; Germann and Aram, 1996; Hofstein, Navon, Kipnis, and Mamlok-Naaman, 2005; Miner, Levy, and Century, 2009; Windschitl, Thompson, and Braaten, 2008; Zohar and Dori, 2003). Through a better understanding of the scientific inquiry process as well as insights into students' struggles with data analysis, we can better understand how to effectively implement strategies in the classroom that encourage the higher order thinking skill of data analysis. This mixed methods, multiple-case study investigated teacher practice in eight high school science inquiry units in the Portland, Oregon metropolitan area and the data analyses that students produced in their accompanying work samples. The results of this study indicate that students struggle to produce proficient analysis and interpretations of data. The areas of student struggle were in the areas that required higher order thinking: analyzing results, drawing conclusions, and communicating results. Furthermore, this research discusses areas of data analysis instruction that may benefit from professional development opportunities.
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14

O'Sullivan, John J. D. "Teach2Learn : gamifying education to gather training data for natural language processing." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/117320.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 65-66).
Teach2Learn is a website which crowd-sources the problem of labeling natural text samples using gamified education as an incentive. Students assign labels to text samples from an unlabeled data set, thereby teaching superised machine learning algorithms how to interpret new samples. In return, students can learn how that algorithm works by unlocking lessons written by researchers. This aligns the incentives of researchers and learners to help both achieve their goals. The application used current best practices in gamification to create a motivating structure around that labeling task. Testing showed that 27.7% of the user base (5/18 users) engaged with the content and labeled enough samples to unlock all of the lessons, suggesting that learning modules are sufficient motivation for the right users. Attempts to grow the platform through paid social media advertising were unsuccessful, likely because users aren't looking for a class when they browse those sites. Unpaid posts on subreddits discussing related topics, where users were more likely to be searching for learning opportunities, were more successful. Future research should seek users through comparable sites and explore how Teach2Learn can be used as an additional learning resource in classrooms.
by John J.D. O'Sullivan
M. Eng.
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15

Koren, Gal M. Eng Massachusetts Institute of Technology. "Senti : a wearable sensor for physiological data acquisition in early education." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/113157.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 79-80).
Wearable sensors have been used in research efforts aiming to develop a mapping between physiological responses of the autonomic nervous system, namely electrodermal activity and heart rate variability, to emotional reactions such as arousal, stress, and attention. While many studies conducted with existing sensors have focused primarily on adults, some have recently begun utilizing them to characterize cognitive and social processes in children. As research in early childhood development continues, a physiological sensor tailored for data acquisition in early education environments, where children spend much of their time socializing and learning, will prove especially valuable for advancing further studies in the field. In this thesis, I present the design and implementation of a compact and lightweight wristband monitor for children, that unobtrusively tracks a set of vital signs that are known to demonstrate sympathetic and parasympathetic responses in the general population. The finalized system is evaluated for data quality and ease of analysis by applying signal processing methods on data collected over a two-week period at a Montessori preschool, where children continuously wore the device each day while engaging in various lesson activities and social interactions.
by Gal Koren.
M. Eng.
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16

Klopfer, Michelle Davis. "Academic Profiles of Science Students: An Analysis of Longitudinal Data on Virginia Students." Diss., Virginia Tech, 2003. http://hdl.handle.net/10919/97401.

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In recent decades, United States public school education has moved toward standards-based curricula. However, performance on standardized tests may not be representative of subject literacy or workforce preparedness. This misalignment may be particularly true in the sciences, where low science literacy and gender-related workforce shortfalls are evident. This study was an exploration of how well standardized test scores and other academic metrics reflected progression to a science major, by gender. This exploratory study used longitudinal data from the Virginia Department of Education, prepared by the Virginia Longitudinal Data System, for students who graduated from Virginia public schools from 2004-2016 (N=1,089,389). Students' standardized assessment scores, science course grades, demographics, and post-secondary major were analyzed using correlation analysis, logistic regression, principal component analysis, and hypothesis testing. Overall, 9% of high school completers enrolled in a post-secondary science major, with approximately half of those students attending 4-year schools. Seventy percent of science majors were female; females were most prevalent in health-related majors and least prevalent in physical sciences. Logistic regression identified the following factors significantly related to enrolling in a post-secondary science major: gender, high school science grades, and the high school's percent of students who majored in science. A student's status as economically disadvantaged or an underrepresented minority was significantly related to enrolling in a 2-year science major. In comparisons among academic metrics, standardized test scores and science grades were uncorrelated, and science grades differed significantly among demographic subgroups. Overall, demographic and school-level factors were more closely related to majoring in science than were academic factors. For both genders and for biological, physical, and health sciences, the percent of students majoring in science doubled from 2005-2015. Standardized test scores and course grades measured different aspects of learning, and higher science grades were related to majoring in science. However, the designation of "science major" is so broad as to be uninformative in a research context; more specificity would be needed to develop academic profiles. From these findings, one can conclude that demographic and cultural factors – rather than academic factors – were more closely related to whether students pursued a science pathway.
Doctor of Philosophy
In recent decades, United States public school education has moved toward standards-based curricula. However, performance on standardized tests may not represent subject knowledge or job preparedness, particularly in the science fields. This study was an exploration of how well standardized test scores and other academic measured were related to majoring in science, for male and female students. This exploratory study used data from the Virginia Department of Education, prepared by the Virginia Longitudinal Data System, for students who graduated from Virginia public schools from 2004-2016. Students' standardized test scores, science course grades, demographics, and college major were analyzed. Overall, 9% of high school completers enrolled in a science major after high school, with approximately half of those students attending 4-year schools. Seventy percent of science majors were female; females were most prevalent in health-related majors and least prevalent in physical sciences. The following factors were significantly related to enrolling in a science major: gender, high school science grades, and the high school's percent of students who majored in science. A student's status as economically disadvantaged or an underrepresented minority was significantly related to enrolling in a 2-year science major. In comparisons among academic measures, standardized test scores and science grades were not related to each other, and science grades differed among demographic groups. Overall, demographic and school-level factors were more closely related to majoring in science than were academic factors. For both genders and for biological, physical, and health sciences, the percent of students majoring in science doubled from 2005-2015. Standardized test scores and course grades measured different aspects of learning, and higher science grades were related to majoring in science. However, the designation of "science major" is so broad as to be uninformative in a research context; more specificity would be needed to develop academic profiles. From these findings, one can conclude that demographic and cultural factors – rather than academic factors – were more closely related to whether students pursued a science pathway.
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17

Klopfer, Michelle D. "Academic Profiles of Science Students: An Analysis of Longitudinal Data on Virginia Students." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/97401.

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Abstract:
In recent decades, United States public school education has moved toward standards-based curricula. However, performance on standardized tests may not be representative of subject literacy or workforce preparedness. This misalignment may be particularly true in the sciences, where low science literacy and gender-related workforce shortfalls are evident. This study was an exploration of how well standardized test scores and other academic metrics reflected progression to a science major, by gender. This exploratory study used longitudinal data from the Virginia Department of Education, prepared by the Virginia Longitudinal Data System, for students who graduated from Virginia public schools from 2004-2016 (N=1,089,389). Students' standardized assessment scores, science course grades, demographics, and post-secondary major were analyzed using correlation analysis, logistic regression, principal component analysis, and hypothesis testing. Overall, 9% of high school completers enrolled in a post-secondary science major, with approximately half of those students attending 4-year schools. Seventy percent of science majors were female; females were most prevalent in health-related majors and least prevalent in physical sciences. Logistic regression identified the following factors significantly related to enrolling in a post-secondary science major: gender, high school science grades, and the high school's percent of students who majored in science. A student's status as economically disadvantaged or an underrepresented minority was significantly related to enrolling in a 2-year science major. In comparisons among academic metrics, standardized test scores and science grades were uncorrelated, and science grades differed significantly among demographic subgroups. Overall, demographic and school-level factors were more closely related to majoring in science than were academic factors. For both genders and for biological, physical, and health sciences, the percent of students majoring in science doubled from 2005-2015. Standardized test scores and course grades measured different aspects of learning, and higher science grades were related to majoring in science. However, the designation of "science major" is so broad as to be uninformative in a research context; more specificity would be needed to develop academic profiles. From these findings, one can conclude that demographic and cultural factors – rather than academic factors – were more closely related to whether students pursued a science pathway.
Doctor of Philosophy
In recent decades, United States public school education has moved toward standards-based curricula. However, performance on standardized tests may not represent subject knowledge or job preparedness, particularly in the science fields. This study was an exploration of how well standardized test scores and other academic measured were related to majoring in science, for male and female students. This exploratory study used data from the Virginia Department of Education, prepared by the Virginia Longitudinal Data System, for students who graduated from Virginia public schools from 2004-2016. Students' standardized test scores, science course grades, demographics, and college major were analyzed. Overall, 9% of high school completers enrolled in a science major after high school, with approximately half of those students attending 4-year schools. Seventy percent of science majors were female; females were most prevalent in health-related majors and least prevalent in physical sciences. The following factors were significantly related to enrolling in a science major: gender, high school science grades, and the high school's percent of students who majored in science. A student's status as economically disadvantaged or an underrepresented minority was significantly related to enrolling in a 2-year science major. In comparisons among academic measures, standardized test scores and science grades were not related to each other, and science grades differed among demographic groups. Overall, demographic and school-level factors were more closely related to majoring in science than were academic factors. For both genders and for biological, physical, and health sciences, the percent of students majoring in science doubled from 2005-2015. Standardized test scores and course grades measured different aspects of learning, and higher science grades were related to majoring in science. However, the designation of "science major" is so broad as to be uninformative in a research context; more specificity would be needed to develop academic profiles. From these findings, one can conclude that demographic and cultural factors – rather than academic factors – were more closely related to whether students pursued a science pathway.
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18

Leech, Andrea Dawn. ""What Does This Graph Mean?" Formative Assessment With Science Inquiry to Improve Data Analysis." PDXScholar, 2014. https://pdxscholar.library.pdx.edu/open_access_etds/1537.

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This study investigated the use of formative assessment to improve three specific data analysis skills within the context of a high school chemistry class: graph interpretation, pattern recognition, and making conclusions based on data. Students need to be able to collect data, analyze that data, and produce accurate scientific explanations (NRC, 2011) if they want to be ready for college and careers after high school. This mixed methods study, performed in a high school chemistry classroom, investigated the impact of the formative assessment process on data analysis skills that require higher order thinking. We hypothesized that the use of evaluative feedback within the formative assessment process would improve specific data analysis skills. The evaluative feedback was given to the one group and withheld from the other for the first part of the study. The treatment group had statistically better data analysis skills after evaluative feedback over the control. While these results are promising, they must be considered preliminary due to a number of limitations involved in this study.
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19

Barrows, Sam George. "Political Responses to Educational Performance Data." Thesis, Harvard University, 2014. http://nrs.harvard.edu/urn-3:HUL.InstRepos:13065019.

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Researchers have found considerable evidence that information about school performance affects people's choices about which schools to send their children to and even where to live. In contrast, little attention has been paid to the effects of school performance information on people's political behavior. Yet Hirschman (1970) famously highlighted the importance of taking seriously not only economic forces, but also the role of "political mechanisms", that is, "non-market forces" or "voice", in analyzing people's responses to school performance and the implications of these responses for school outcomes. This dissertation explores the effect of information about student and school performance on people's political attitudes and behavior. I first present findings from an original dataset of school board elections in Florida that indicate that voters fail to punish school board incumbents in response to information signaling poor school performance. There is even evidence that voters sometimes reward incumbents for failure. I next analyze a dataset that links student test scores in England to a subsequent survey, and find that that informational signals about individual student performance can have long−lasting effects on parental behavior. Finally, I analyze the results of a survey experiment administered to a nationally representative sample of Americans, and find that information about the relative performance of local schools depresses average perceptions of local school quality and increases support for school reforms.
Government
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Grgurina, Nataša. "Computational thinking in Dutch secondary education." Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2013/6455/.

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We shall examine the Pedagogical Content Knowledge (PCK) of Computer Science (CS) teachers concerning students’ Computational Thinking (CT) problem solving skills within the context of a CS course in Dutch secondary education and thus obtain an operational definition of CT and ascertain appropriate teaching methodology. Next we shall develop an instrument to assess students’ CT and design a curriculum intervention geared toward teaching and improving students’ CT problem solving skills and competences. As a result, this research will yield an operational definition of CT, knowledge about CT PCK, a CT assessment instrument and teaching materials and accompanying teacher instructions. It shall contribute to CS teacher education, development of CT education and to education in other (STEM) subjects where CT plays a supporting role, both nationally and internationally.
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Whitlock, Joshua Lee. "Using Data Science and Predictive Analytics to Understand 4-Year University Student Churn." Digital Commons @ East Tennessee State University, 2018. https://dc.etsu.edu/etd/3356.

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The purpose of this study was to discover factors about first-time freshmen that began at one of the six 4-year universities in the former Tennessee Board of Regents (TBR) system, transferred to any other institution after their first year, and graduated with a degree or certificate. These factors would be used with predictive models to identify these students prior to their initial departure. Thirty-four variables about students and the institutions that they attended and graduated from were used to perform principal component analysis to examine the factors involved in their decisions. A subset of 18 variables about these students in their first semester were used to perform principal component analysis and produce a set of 4 factors that were used in 5 predictive models. The 4 factors of students who transferred and graduated elsewhere were “Institutional Characteristics,” “Institution’s Focus on Academics,” “Student Aptitude,” and “Student Community.” These 4 factors were combined with the additional demographic variables of gender, race, residency, and initial institution to form a final dataset used in predictive modeling. The predictive models used were a logistic regression, decision tree, random forest, artificial neural network, and support vector machine. All models had predictive power beyond that of random chance. The logistic regression and support vector machine models had the most predictive power, followed by the artificial neural network, random forest, and decision tree models respectively.
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Weise, Martin. "A model for teaching informatics to German secondary school students in English-language bilingual education." Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2013/6456/.

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Informatics as a school subject has been virtually absent from bilingual education programs in German secondary schools. Most bilingual programs in German secondary education started out by focusing on subjects from the field of social sciences. Teachers and bilingual curriculum experts alike have been regarding those as the most suitable subjects for bilingual instruction – largely due to the intercultural perspective that a bilingual approach provides. And though one cannot deny the gain that ensues from an intercultural perspective on subjects such as history or geography, this benefit is certainly not limited to social science subjects. In consequence, bilingual curriculum designers have already begun to include other subjects such as physics or chemistry in bilingual school programs. It only seems a small step to extend this to informatics. This paper will start out by addressing potential benefits of adding informatics to the range of subjects taught as part of English-language bilingual programs in German secondary education. In a second step it will sketch out a methodological (= didactical) model for teaching informatics to German learners through English. It will then provide two items of hands-on and tested teaching material in accordance with this model. The discussion will conclude with a brief outlook on the chances and prerequisites of firmly establishing informatics as part of bilingual school curricula in Germany.
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Coffman, Mitchell Ward. "A National Study of the Relationship between Home Access to a Computer and Academic Performance Scores of Grade 12 U.S. Science Students| An Analysis of the 2009 NAEP Data." Thesis, University of Louisiana at Lafayette, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10163258.

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The purpose of this dissertation was to examine the relationship between student access to a computer at home and academic achievement. The 2009 National Assessment of Educational Progress (NAEP) dataset was probed using the National Data Explorer (NDE) to investigate correlations in the subsets of SES, Parental Education, Race, and Gender as it relates to access of a home computer and improved performance scores for U.S. public school grade 12 science students. A causal-comparative approach was employed seeking clarity on the relationship between home access and performance scores. The influence of home access cannot overcome the challenges students of lower SES face. The achievement gap, or a second digital divide, for underprivileged classes of students, including minorities does not appear to contract via student access to a home computer. Nonetheless, in tests for significance, statistically significant improvement in science performance scores was reported for those having access to a computer at home compared to those not having access. Additionally, regression models reported evidence of correlations between and among subsets of controls for the demographic factors gender, race, and socioeconomic status. Variability in these correlations was high; suggesting influence from unobserved factors may have more impact upon the dependent variable. Having access to a computer at home increases performance scores for grade 12 general science students of all races, genders and socioeconomic levels. However, the performance gap is roughly equivalent to the existing performance gap of the national average for science scores, suggesting little influence from access to a computer on academic achievement. The variability of scores reported in the regression analysis models reflects a moderate to low effect, suggesting an absence of causation. These statistical results are accurate and confirm the literature review, whereby having access to a computer at home and the predictor variables were found to have a significant impact on performance scores, although the data presented suggest computer access at home is less influential upon performance scores than poverty and its correlates.

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Edeljung, Johan. "Making Exception Information Understandable for Persons without Computer Science Education : Improving the Software by Analyzing Exceptions Data." Thesis, Umeå universitet, Institutionen för datavetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-128574.

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This thesis consider exceptions from a different (maybe unique) perspective. Not talking about how and if they should be handled, instead it purposes ideas how to analyze exception data. Both in an analytical way, by plotting large amount of exception information with different parameters, and also by seeing if the information that each exception object carries can be made available for others than developers. These analyses are made available because of a centralized database, filled with exception data, that the software company Vitec has. The method used to evaluate these analyses, was to develop an application, that could perform such analysis. A model to translate the exception information was also developed, and the resulting translations was integrated with the application. Tests to evaluate how useful the outcome could be for the target users, developers and support personnel of Vitec, was conducted. The conclusion of this work was that in fact both types of analyses can help improve the software. The translations by allowing the support personnel to faster resolve the issues at hand, and taking some of the burden of the developers. The charts plots can assist the developers to see how a system is working, and where the most errors occurs. The work answered the question if there would be any use of such analysis and translation of exception, however, in answering these questions opened the door to a new big question. How can the analyses and translations be done in the best way? The thesis discuss this matter as well, but this work has just started and as but the investigations, strongly suggest ,further work would be beneficial.
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Durr, Angel Krystina. "A Text Analysis of Data Science Career Opportunities and U.S. iSchool Curriculum." Thesis, University of North Texas, 2018. https://digital.library.unt.edu/ark:/67531/metadc1404565/.

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Data science employment opportunities of varied complexity and environment are in growing demand across the globe. Data science as a discipline potentially offers a wealth of jobs to prospective employees, while traditional information science-based roles continue to decrease as budgets get cut across the U.S. Since data is related closely to information historically, this research will explore the education of U.S. iSchool professionals and compare it to traditional data science roles being advertised within the job market. Through a combination of latent semantic analysis of over 1600 job postings and iSchool course documentation, it is our aim to explore the intersection of library and information science and data science. Hopefully these research findings will guide future directions for library and information science professionals into data science driven roles, while also examining and highlighting the data science techniques currently driven by the education of iSchool professionals. In addition, it is our aim to understand how data science could benefit from a mutually symbiotic relationship with the field of information science as statistically data scientists spend far too much time working on data preparation and not nearly enough time conducting scientific inquiry. The results of this examination will potentially guide future directions of iSchool students and professionals towards more cooperative data science roles and guide future research into the intersection between iSchools and data science and possibilities for partnership.
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Gaddis, Margaret L. "Training Citizen Scientists for Data Reliability| A Multiple Case Study to Identify Themes in Current Training Initiatives." Thesis, The University of the Rockies, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=13423764.

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This dissertation characterized trainings designed to prepare citizen scientists to collect ecological data in natural outdoor settings. Citizen scientists are volunteers who participate in scientific activities under the guidance of professional scientists and organizations. The work of citizen scientists greatly expands the data collection possibilities in natural resource management and increases science literacy among participants and their social communities. The general problem is that some scientists and land managers view the data collected by citizen scientists as unreliable. The specific problem is the absence of educational training measurement in citizen science program design and analysis with which to ascertain the learning gains of trained citizen scientists.

Through a sequenced methodology of data analysis, survey, and semi-structured interviews, deductive descriptors and codes guided a directed content analysis of data collected. The analysis indicated strong alignment between citizen science, andragogy, and social learning theory. The sample revealed a bimodal distribution related to the type of data collected and the subsequent training design. Little training existed when data collection involved photography only. Citizen scientists brought prior skills to the task but did not need to gain new procedural learning to complete their data collection task. When citizen scientists collected more complex measurements, classroom and field mentoring facilitated learning.

Citizen science leaders described their perception of the reliability of their citizen scientists’ data collection efforts. Computer technologies validated photo and water quality data. Therefore, quantitative data analysis supported the perception of data reliability. Terrestrial data had a range of reliability qualifications including video and paper quizzing, field observation of methods implemented, periodic data checks, and follow-up mentoring when data quality was poor. Managers of terrestrial citizen science programs were confident in the reliability of the data for the land management, policy, and research applications required.

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Mann, Gillian Margaret. "Efficiency evaluations of North American university libraries by data envelopment analysis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ29750.pdf.

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Sarker, Farhana. "Linked data technologies to support higher education challenges : student retention, progression and completion." Thesis, University of Southampton, 2014. https://eprints.soton.ac.uk/374317/.

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Around the world, higher education institutions are facing a growing number of challenges. In recent decades, considerable interest has emerged on identifying those challenges and proposing efficient ways to address them. This thesis reviews a wide range of literature on higher education challenges and identifies related intuitional data, data repositories and external open data sources to address these challenges. It subsequently explores whether certain higher education challenges and in particular student retention, progression and completion can be better addressed using data from various data sources and the recent development of technologies such as, data analytics and linked data. Traditionally, research in this area is survey-based and survey-based studies have some drawbacks such as, low participation rate and the high cost associated with it. This research sought to overcome these problems. To this end, two experiments were conducted. The first experiment examined the sufficiency of linked data and external open data sources to develop blended prediction models to predict at-risk students in their first year of study. The result based on 149 undergraduate students’ data, established that prediction models based on institutional repositories and external open data perform better than survey-based one. The second experiment examined the capabilities of institutional repositories and external open data sources in predicting students’ first year marks and established that models using institutional repositories and external open data sources can perform better than models based on only institutional repositories. In order to examine the capabilities of linked data, external open data and data analytics, a data integration and analytics environment was deployed. The four key contributions of this thesis are: (1) it presents a comprehensive list of higher education challenges and required data and data repositories to address these challenges; (2) it demonstrates how external open data sources can be used to accurately predict students at-risk and students’ first year marks; (3) it shows how including external open data sources in prediction models can increase the overall model accuracy and (4) it establishes the strengths and weaknesses of linked data to support in employing data analytics for predictive models in student retention, progression and completion.
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Lewis, Sharon, and University of Lethbridge Faculty of Education. "Using telecommunications to enhance the grade 8 science curriculum." Thesis, Lethbridge, Alta. : University of Lethbridge, Faculty of Education, 1996, 1996. http://hdl.handle.net/10133/31.

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The primary objective of this study was to implement a project that utilizes telecommunications as a tool to enhance the grade eight science curriculum. The process of becoming prepared to undertake this study was examined and documentd so that teachers in all subject areas at all grade levels could use it as a guide for similar projects. It was proposed to do this by conducting a collaborative project in which the students would use the scientific method to develop research questions that could be used to discover why the incidence of asthma is so high in Central Alberta. These questions would be sent out to schools across Canada and then the data would be analyzed and interpreted. The results would be shared with all participants as well as asthma researchers. The study met with many barriers whcih impeded the progress as well as made it impossible to fulfil the original goal of having the students collaborate with the experts and contribute their own research to the field. Whe embarking on a new project using technology it is inevitable that there will be barriers. Through repeated reconnaissance we were able to adjust our goals and still pursue very worthwile, but very different computer and telecommunications projects. The students attitudes towards learning science, science in society and computers were measured by pre and post surveys. The findings showed that the students were aware of the importance of all these factors in their lives. Without completing the asthma study, it is impossible to know how much of a difference there would have been in the results. The qualitative results showed very clearly that computers are a motivator for students. They enjoy working on them and the challenge they present. Many of them will do extra homework so that they can take advantage of every opportunity to work on the computer. Unfortunately, many teachers do not have the time or support to learn enough about the Internet/Schoolnet and what is available to take full advantage of what is has to offer our students and ourselves. For the most part, there are few teachers in each disrict becoming involved. This will change over time only if there is a support system in place and the pioneers share what they have learned. We cannot run the risk of the forerunners becoming discouraged and giving up. The Internet is a global community. For that community to grow and flourish we must share what we have learned and provide the means to make the path smoother for those who follow. Through this study, the projects have been documented and resources have been prepared that are intended to help others get online and access a wide variety of resources that are sure to enhance all programs and professional development.
xiii, 228 leaves : ill. ; 28 cm.
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Hall-Ellis, Sylvia. "Employers' Expectation for Entry-Level Catalog Librarians: What Position Announcement Data Indicate." Association for Library and Information Science Education, 2005. http://hdl.handle.net/10150/106147.

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This is a PowerPoint presentation (33 slides) on Wednesday January 12, 2005 in Session 4.2: Electronic Resources: Current Practices, Employer Expectations, and Teaching Strategies, sponsored by the Technical Services Education SIG at the 2005 ALISE Conference, Boston, MA. In order to prepare entry-level catalogers and offer cataloging-related courses, this research identifies the technical skills and competencies that a student should possess for entering the library world. It reviews 495 position announcements for catalog librarians from September 1, 2000 and August 31, 2003 and presents some useful observations. By evaluating the findings, this research makes suggestions to the development of a core curriculum in cataloging education.
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Zhao, Hui. "School expectations and initiatives for parental involvement in 30 nations a comparative study using TIMSS 1999 data /." Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/4851.

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Thesis (Ph. D.)--University of Missouri-Columbia, 2007.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on October 16, 2007) Vita. Includes bibliographical references.
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Luke, Joseph Abraham. "Continuously Collecting Software Development Event Data As Students Program." Thesis, Virginia Tech, 2015. http://hdl.handle.net/10919/52976.

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Teaching good software development practices is difficult, both in theory and in practice. Time management and project organization are skills often left by the wayside by students too focused on the coding itself. Educational research has been invested in developing strategies to combat these bad habits. In order to provide better support for interventions discouraging bad development habits, more data about student development is needed. The purpose of this research is to design and implement software to collect data continuously as students work on programming projects and provide it in useful forms to instructors and researchers so that they may make headway in designing new curricula, assignments, and interventions that better help students to succeed. The DevEventTracker is a software system that interfaces with existing Web-CAT services to track student development data continuously, without any student effort. Development and compilation events are tracked within the Eclipse IDE through a plugin and sent to a Web-CAT server. Code snapshots corresponding to each event are also committed to a server-side repository. The system provides a dashboard as a set of instructor-visible web pages that display useful data in generated charts and tables. Data are presented in both class overview and individual student summaries. The system presented will enable future research in education and specifically in intervention development. Particularly, the system can be used to allow instructors to identify students who have a tendency to procrastinate and design more effective interventions.
Master of Science
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Lessner, Daniel. "The role of algorithm in general secondary education revisited." Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2013/6453/.

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The traditional purpose of algorithm in education is to prepare students for programming. In our effort to introduce the practically missing computing science into Czech general secondary education, we have revisited this purpose.We propose an approach, which is in better accordance with the goals of general secondary education in Czechia. The importance of programming is diminishing, while recognition of algorithmic procedures and precise (yet concise) communication of algorithms is gaining importance. This includes expressing algorithms in natural language, which is more useful for most of the students than programming. We propose criteria to evaluate such descriptions. Finally, an idea about the limitations is required (inefficient algorithms, unsolvable problems, Turing’s test). We describe these adjusted educational goals and an outline of the resulting course. Our experience with carrying out the proposed intentions is satisfactory, although we did not accomplish all the defined goals.
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Jakupovic, Jasmin. "Educated to Learn : How to enhance the education of computer science and informatics." Thesis, Tekniska Högskolan, Högskolan i Jönköping, JTH. Forskningsmiljö Datavetenskap och informatik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-31902.

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The very nature of computer science with its constant changes forces those who wish to follow to adapt and react quickly. Large companies invest in being up to date in order to generate revenue and stay active on the market. Universities, on the other hand, need to imply same practices of staying up to date with industry needs in order to produce industry ready engineers. By interviewing former students, now engineers in the industry, and current university staff this thesis aims to learn if there is space for enhancing the education through different lecturing approaches and/or curriculum adaptation and development. In order to address these concerns a qualitative research has been conducted, focusing on data collection obtained through semi-structured live world interviews. The method used follows the seven stages of research interviewing introduced by Kvale and focuses on collecting and preparing relevant data for analysis. The collected data is transcribed, refined, and further on analyzed in the “Findings and analysis” chapter. The focus of analyzing was answering the three research questions; learning how higher education impacts a Computer Science and Informatics Engineers’ job, how to better undergo the transition from studies to working in the industry and how to develop a curriculum that helps support the previous two. Unaltered quoted extracts are presented and individually analyzed. To paint a better picture a theme-wise analysis is presented summing valuable themes that were repeated throughout the interviewing phase. The findings obtained imply that there are several factors directly influencing the quality of education. From the student side, it mostly concerns expectation and dedication involving studies, and from the university side it is commitment to the curriculum development process. Due to the time and resource limitations this research provides findings conducted on a narrowed scope, although it can serve as a great foundation for further development; possibly as a PhD research.
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Doyle, Jacqueline. "Describing and Mapping the Interactions between Student Affective Factors Related to Persistence in Science, Physics, and Engineering." FIU Digital Commons, 2017. http://digitalcommons.fiu.edu/etd/3353.

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This dissertation explores how students’ beliefs and attitudes interact with their identities as physics people, motivated by calls to increase participation in science, technology, engineering, and mathematics (STEM) careers. This work combines several theoretical frameworks, including Identity theory, Future Time Perspective theory, and other personality traits to investigate associations between these factors. An enriched understanding of how these attitudinal factors are associated with each other extends prior models of identity and link theoretical frameworks used in psychological and educational research. The research uses a series of quantitative and qualitative methodologies, including linear and logistic regression analysis, thematic interview analysis, and an innovative analytic technique adapted for use with student educational data for the first time: topological data analysis via the Mapper algorithm. Engineering students were surveyed in their introductory engineering courses. Several factors are found to be associated with physics identity, including student interest in particular engineering majors. The distributions of student scores on these affective constructs are simultaneously represented in a map of beliefs, from which the existence of a large “normative group” of students (according to their beliefs) is identified, defined by the data as a large concentration of similarly minded students. Significant differences exist in the demographic representation of this normative group compared to other students, which has implications for recruitment efforts that seek to increase diversity in STEM fields. Select students from both the normative group and outside the normative group were selected for subsequent interviews investigating their associations between physics and engineering, and how their physics identities evolve during their engineering careers. Further analyses suggest a more complex model of physics and engineering identity which is not necessarily uniform for all engineering students, including discipline-specific differences that should be further investigated. Further, the use of physics identity as a model to describe engineering student choices may be limited in applicability to early college. Interview analysis shows that physics recognition beliefs become contextualized in engineering as students begin to view physics as an increasingly distinct domain from engineering.
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Gujberová, Monika, and Peter Tomcsányi. "Environments for programming in primary education." Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2013/6449/.

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The aim of our article is to collect and present information about contemporary programming environments that are suitable for primary education. We studied the ways they implement (or do not implement) some programming concepts, the ways programs are represented and built in order to support young and novice programmers, as well as their suitability to allow different forms of sharing the results of pupils’ work. We present not only a short description of each considered environment and the taxonomy in the form of a table, but also our understanding and opinions on how and why the environments implement the same concepts and ideas in different ways and which concepts and ideas seem to be important to the creators of such environments.
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Reisenhofer, Matthew Phillip. "A comparative analysis of three manufacturers of science probeware for the classroom." CSUSB ScholarWorks, 2006. https://scholarworks.lib.csusb.edu/etd-project/3035.

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Evaluates and assesses the probes and associated probeware of three manufacturers using a variety of criteria that are essential information for a consumer. The probes and probeware examined include Pasco Scientific's ScienceWorkshop, Venier's LabPro, and Onset's HOBO. Three experiments were used to test each of the criteria for comparison. Based on the data in the study no manufacturer proved themselves to be clearly the best, and taken collectively the benefits and drawbacks balance out.
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Saulnier, Christopher R. "Exploring design based wilderness education : a pedagogy to develop design thinking, an engineering science worldview, and leadership capacity." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/103575.

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Thesis: S.M. in Technology and Policy, Massachusetts Institute of Technology, Institute for Data, Systems, and Society, Technology and Policy Program, 2015.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 80-84).
This study explores the experience of students during the implementation of a design-based wilderness education curricula. I introduce the concept of a curriculum that combines the pedagogies of design-based learning and wilderness education to encourage the development of design thinking, an engineering science worldview, and leadership ability. This project bridges the gap between the wilderness education and engineering education literature as this is a novel approach to engineering education. In bridging the two literatures, we find that the outcomes of wilderness education align well with the contemporary demands of engineering education. The initial implementation of the design-based wilderness education curriculum took place in the Summer of 2014. Thirty students from the Singapore University of Technology and Design and six students from MIT participated in the program. A mixed-methods study was performed, relying on surveys, exit interviews, and instructor observations. The findings from the research illustrate that design-based wilderness education holds the potential to serve as an exciting novel avenue to encourage design thinking, the development of an engineering science worldview, and leadership ability. While further research is necessary, this initial exploration finds that wilderness education is a promising vector for supporting effective design thinking practices and the development of an engineering science worldview, alongside leadership ability.
by Christopher R. Saulnier.
S.M. in Technology and Policy
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Wang, Hao, and Yun Xie. "The use of Online Social Networks in Chinese Collaborative E-learning Education." Thesis, Örebro universitet, Handelshögskolan vid Örebro universitet, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-16037.

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Hon, Yuen-sing Vincent. "Effectiveness of the changes in the Hong Kong mathematics curriculum an analysis of the trends in international mathematics and science study data /." Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B35418072.

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Gülbahar, Yasemin, Mustafa Ilkhan, Selcan Kilis, and Okan Arslan. "Informatics education in Turkey : national ICT curriculum and teacher training at elementary level." Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2013/6451/.

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This article is a summary of the work carried out by the Ministry of Education in Turkey, in terms of the development of a new ICT Curriculum, together with the e-Training of teachers who will play an important role in the forthcoming pilot study. Based on recent literature on the topic, the article starts by introducing the “F@tih Project”, a national project that aims to effectively integrate technology into schools. After assessing teachers’ and students’ ICT competencies, as defined internationally, the review continues with the proposed model for the e-training of teachers. Summarizing the process of development of the new ICT curriculum, researchers underline key points of the curriculum such as dimensions, levels and competencies. Then teachers’ e-training approaches, together with selected tools, are explained in line with the importance and stages of action research that will be used throughout the pilot implementation of the curriculum and e-training process.
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Lamons, Julia Lorie. "An Analysis of Data Collected from the 2007-2008 Tennessee State Report Card and the Variables Related to Science Test Results." Digital Commons @ East Tennessee State University, 2009. https://dc.etsu.edu/etd/1848.

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The purpose of this study was to determine whether Tennessee Comprehensive Assessment Program (TCAP) Achievement reading scores, school district per-pupil expenditures, school size, percentage of students qualifying for free and reduced-priced meals, and attendance were related to science TCAP test scores from the 2007-2008 school year. The data were gathered from an analysis of mean standardized test scores in reading and science of 8th graders in 67 school systems comprising 181 schools located throughout Tennessee. One hundred eighty-one schools configured grades 6 through 8 were used in this study. Only 177 schools had reported attendance available on the Tennessee Department of Education website. Pearson correlations were performed between the 8th mean grade science TCAP scores and 8th grade mean reading scores, per-pupil expenditure, school size, attendance, and the percentage of students qualifying for free and reduced-priced meals. Independent-samples t tests were conducted to evaluate whether 8th grade mean science TCAP scores and 8th grade mean reading scores varied depending on whether the school per-pupil expenditure was above or below the state average of $8,345. Independent-samples t test were also conducted to evaluate whether 8th grade mean science TCAP scores and 8th grade mean reading scores varied depending on whether the school attendance percentage was above or below the state goal of 93%. The school characteristic with the strongest association with the mean 8th grade science TCAP scores as computed by Pearson's correlation is the mean 8th grade reading TCAP scores. The values can be ranked as follows: mean 8th grade reading scores (.92) > percentage of students qualifying for free and reduced meals (-.84) > per-pupil expenditure (-.62) > attendance (.60) > school size (.23).
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Robertson, Laura, Pamela Cromie, and Mahua Chakraborty. "Scientific Practice: Data Analysis by Middle School and High School Students." Digital Commons @ East Tennessee State University, 2015. https://dc.etsu.edu/etsu-works/773.

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Matlatse, Refiloe. "An Evaluation of a structured training event aimed at enhancing the Research Data Management Knowledge and Skills of Library and Information Science Professionals in South African Higher Education Institutions." Diss., University of Pretoria, 2016. http://hdl.handle.net/2263/58393.

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Research Data Management (RDM) has received a lot of attention recently. In South Africa, the importance of RDM has amplified since the release of the National Research Foundation‟s (NRF) open access statement. According to the statement, researchers who receive funding from the NRF must deposit their research output in an open access (OA) repository. In addition, the data supporting the research should be deposited in an accredited OA repository with a Digital Object Identifier (DOI) for future citations (NRF, 2015: online). The mandate, along with other drivers such as research data re-use, increased impact and validation of research findings has forced institutions to investigate the possibility of offering RDM services in their institutions (Ashley, 2012). It is expected that libraries and Library and Information Science (LIS) professionals will initiate and support RDM in their institutions. LIS professionals will need to upgrade or obtain new skills and knowledge to fulfil their new roles and responsibilities. Various training opportunities are available to interested professionals to improve their knowledge and skills related to RDM. These can be as simple as a workshop or as complex as a university degree. The objective of this research was to identify and evaluate a RDM training intervention to determine whether the training intervention could enhance the knowledge and skills of LIS professionals in South African (SA) Higher Education Institutions (HEIs). An embedded research design was used to investigate whether an RDM workshop, hosted by the Network for Data and Information Curation Communities (NeDICC), could enhance the LIS professional‟s (participants) perception of their RDM understanding, knowledge and skills. The research found that the RDM workshop was highly successful in enhancing the participant‟s perception of their RDM understanding and knowledge. The RDM workshop was less successful in enhancing the participant‟s perception of their RDM skills. It was recommended that LIS professionals (1) take advantage of the online RDM training material available to enhance their understanding and knowledge of RDM; (2) attend face-to-face training interventions to enhance or develop their RDM skills and (3) enrol in university level educational programmes to gain a qualification in RDM if they qualify. It was also recommended that institutions that provide RDM training should focus on specific aspects of RDM instead of offering a general overview. This research can be used to inspire larger studies or studies that compare two or more RDM training interventions.
Mini Dissertation (MIT)--University of Pretoria, 2016.
Carnegie Corporation of New York
University of Pretoria
Information Science
MIT
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45

Hofuku, Yoyoi, Shinya Cho, Tomohiro Nishida, and Susumu Kanemune. "Why is programming difficult? : proposal for learning programming in “small steps” and a prototype tool for detecting “gaps”." Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2013/6445/.

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In this article, we propose a model for an understanding process that learners can use while studying programming. We focus on the “small step” method, in which students learn only a few concepts for one program to avoid having trouble with learning programming. We also analyze the difference in the description order between several C programming textbooks on the basis of the model. We developed a tool to detect “gaps” (a lot of concepts to be learned in a program) in programming textbooks.
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46

Hellmuth, Wayne J. "Design theory for innovation of classroom-based information systems." Thesis, Queensland University of Technology, 2015. https://eprints.qut.edu.au/87824/1/Wayne_Hellmuth_Thesis.pdf.

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This research used design science research methods to develop, instantiate, implement, and measure the acceptance of a novel software artefact. The primary purpose of this software artefact was to enhance data collection, improve its quality and enable its capture in classroom environments without distracting from the teaching activity. The artefact set is an iOS app, with supporting web services and technologies designed in response to teacher and pastoral care needs. System analysis and design used Enterprise Architecture methods. The novel component of the iOS app implemented proximity detection to identify the student through their iPad and automatically link to that student's data. The use of this novel software artefact and web services was trialled in a school setting, measuring user acceptance and system utility. This integrated system was shown to improve the accuracy, consistency, completeness and timeliness of captured data and the utility of the input and reporting systems.
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47

Stenliden, Linnéa. "Visual Storytelling Interacting in School : Learning Conditions in the Social Science Classroom." Doctoral thesis, Linköpings universitet, Lärande, Estetik, Naturvetenskap (LEN), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-106885.

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The aim of this compilation thesis is to understand how technology for visual storytelling can be shaped and used in relation to social science education in primary school, but also how social dimensions, technical and other matters create emerging learning conditions in such an educational setting. The visual storytelling technology introduced and used in the study is ‘the Statistics eXplorer platform, a geovisual analytics. The choice of theoretical perspectives to inform and guide the study is a socio-cultural view of human action, but also actor network theory is used to take account also of activities of technology and other matters. The study builds on three empirical materials that generate data from 16 social science teachers, and 126 students from five social science classrooms, in three Swedish primary schools. It contains field notes from the introduction of the technology; focusgroup interviews with teachers; think-aloud interviews with students and two kinds of video recordings from the classrooms (with an ordinary video camera and with software that capture activities at the computer screen, students’ activities and the audio as well). The analysis shows that the visual storytelling technology is shaped in relevant ways for social science teachers. The analysis also illustrates that the visual educational material are usable for primary school students in their social science education. They illustrate further how teachers, students, technology, information, tasks, data types, etc. together and in in close relation create highly complex learning conditions. The technology can therefore be seen as appropriate for the educational practice, but the complexity together with students’ apprehension of how to announce knowledge distribute severe problem spaces in the learning activities. The technology can therefore be assumed as a catalyst for educational change, but to achieve its potentials, reflections on didactic design and knowledge formation is requested to support the quality of students’ knowledge in relation to visual analysis.
Syftet i denna avhandling är, att förstå hur teknik för visual storytelling kan vara utformad och användas i relation till samhällsorienterande undervisning i grundskolan (årskurs 4 – 6), men också hur sociala dimensioner, tekniska och andra faktorer skapar villkor för lärande i ett sådant undervisningssammanhang. I studien introduceras datavisualiseringsteknik för visual storytelling: ‘the Statistics eXplorer platform’, ett geovisual analytics. Den teoretiska referensramen har sin grund i ett social konstruktionistiskt synsätt Ett socio-kulturellt perspektiv används för att analysera social aktivitet, men även aktörnätverks teori används för att analysera både sociala och materiella aktörer. Avhandlingen bygger på tre empiriska material som genereras med hjälp av 16 lärare i samhällsorienterande ämnen, och 126 elever tillhörande fem olika klassrum i tre olika svenska grundskolor. Materialet innehåller: fältanteckningar ifrån introduktion av tekniken, fokusgrupps-intervjuer med lärare, ‘tänka högt’-intervjuer med elever och två sorters videoinspelningar ifrån klassrum (dels med vanlig videokamera och dels med mjukvara som spelar in aktiviteter på datorskärmen och elevernas aktiviteter vid datorn, liksom ljudet). Analysen visar hur lärare, elever, teknik, information, uppgifter, data-typer, etc. tillsammans, i nära samarbete i de studerade klassrummen, skapar mycket komplexa villkor för lärande. De läraktiviteter som uppstår i klassrummen där teknik för visuell analys inkluderas, erbjuder elever support att: hantera stora datamängder, bli delaktiga i olika läraktiviteter och uppnå olika utbildningsmål, men även andra sorters elevrelaterade mål. Därför kan tekniken sägas vara relevant för denna sorts undervisning. Vidare visar analysen hur komplexiteten tillsammans med elevernas uppfattningar av hur kunskap skall visas, skapar påtagliga ‘problem spaces’ i läraktiviteterna. Lärandevillkoren kan därför förstås som en klassrumspraktik som inte fullt ut överensstämmer med den introducerade teknikens erbjudanden för visuell analys. Därför efterfrågas en förändrad syn på didaktisk design och elevers kunskapsformering, vilket blir betydelsefullt för kunskapens kvalitet i förhållande till visuell analys.
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48

Harshman, Jordan T. "Characterizing High School Chemistry Teachers' Use of Formative Assessment Data to Improve Teaching." Miami University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=miami1437652616.

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49

Meenakshi, Renganathan Siva. "An Interactive Learning Tool for Early Algebra Education: Design, Implementation, Evaluation and Deployment." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1492659130106009.

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50

Bohren, Janet Linderoth. "A nine month study of graph construction skills and reasoning strategies used by ninth grade students to construct graphs of science data by hand and with computer graphing software /." The Ohio State University, 1988. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487588249823852.

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