Supporting Students’ Basic Science Process Skills by Augmented Reality Learning Media

Science process skills (SPS) are one of the skills needed in the chemistry learning process, in order to gain a complete understanding of the concepts. This skills categorized into two types; basic and integrated. This research aimed to develop a product of Augmented Reality (AR) learning media then to know its feasibility, practicality, and effectiveness on students’ basic SPS on acid base learning. The research adopted Research and Development (R&D) with 4-D model consisted of define, design, develop, and disseminate stages. Questionnaire was used to measure the feasibility and practicality. Then, the obtained data were analyzed by qualitative and quantitative descriptive. In addition, SPS test was used to measure the effectiveness of AR learning media and the data were analyzed by the test of One-way ANOVA, Tukey’s Post Hoc test, and General Linear Model (GLM) Univariate. The result showed that the AR learning media is feasible, practical, and effective with big influence to support students’ basic SPS on acid base learning

An investigation into supporting the teaching of calculus-based senior mathematics in Queensland

David Chinofunga investigated student participation in calculus-based senior secondary mathematics in Queensland and pedagogical resources that enhance teaching of mathematics. Trend analysis reveal a high dropout rate. David also found that pedagogical resources that comprise procedural flowcharts and concept maps can enrich mathematics teaching and promote student participation and engagement

Kohti automaattisia vihjeitä visuaalisessa algoritmisimulaatiossa

Visual Algorithm Simulation (VAS) exercise is an interactive application, which teaches an algorithm or a data structure. The exercise shows the student a visual representation of a data structure with initial data. The student imitates the execution of the algorithm by interacting with the visual representation. The student's solution is graded automatically. A misconception about the algorithm being learned can manifest itself as systematic errors, which can be modelled as a new algorithm. It is assumed that a VAS exercise, which could detect automatically a misconception and give corrective feedback would further support learning. This thesis includes a literature review on algorithm misconceptions and an empirical study. Four VAS exercises of OpenDSA e-textbook are reviewed by their program code: Evaluating a postfix expression, Build heap, Quicksort, and Dijkstra's algorithm. A dataset of 1430 Build heap VAS submissions is analysed manually with ad-hoc software. The submissions are then automatically classified based on the misconceptions found. The main result extends the set of known misconceptions of the Build-heap VAS exercise. 52 percent of the submissions were correct, 17 percent were misconceptions and the rest 31 percent had a lo0gical explanation. 95 per cent of submissions classified as misconception have multiple explanations with heap size of 10. The thesis presents a Python software, which can automatically classify the known misconceptions. Theory on how to generate VAS inputs, which support detection of misconceptions is discussed. The theory is applied by improving the input generation of Dijkstra's algorithm exercise. The thesis concludes that studying misconceptions in the VAS exercises of OpenDSA currently requires exercise-dependent work. Not all OpenDSA VAS exercises record enough data for later analysis. Moreover, the player and analysis software must be written separately for each exercise. There is need to develop the OpenDSA related software libraries to produce detailed exercise recordings. It should be studied how the heap size in the Build-heap exercise affects detection of misconceptions.Visuaalinen algoritmisimulaatiotehtävä (VAS-tehtävä) on vuorovaikutteinen sovellus, joka opettaa algoritmin tai tietorakenteen. Tehtävä näyttää opiskelijalle kuvan tietorakenteesta lähtödatalla. Opiskelija mukailee algoritmin suoritusta vuorovaikuttamalla kuvaesityksen kanssa. Opiskelijan ratkaisu arvostellaan automaattisesti. Väärinkäsitys VAS-tehtävässä on opiskelijan järjestelmällinen väärinymmärrys, joka voidaan kuvata algoritmilla. On oletus, että VAS-tehtävä, joka tunnistaisi automaattisesti väärinkäsityksen ja antaisi korjaavaa palautetta, tukisi oppimista entisestään. Tämä opinnäytetyö sisältää kirjallisuustutkimuksen algoritmien väärinkäsityksistä sekä empiirisen tutkimuksen. Sähköisen OpenDSA-kirjan neljä VAS-tehtävää on tutkittu niiden ohjelmakoodiltaan: Postfix-lausekkeen evaluointi, binäärikeon rakentaminen, pikajärjestäminen ja Dijkstran algoritmi. Tietoaineisto, jossa on 1430 tallennetta Binäärikeon rakentaminen -tehtävästä, on analysoitu käsin tätä varten kehitetyllä ohjelmalla. Tallenteet on sitten automaattisesti luokiteltu löydettyjen väärinkäsitysten perusteella. Työn päätulos laajentaa binäärikeon rakentaminen -tehtävän väärinkäsityksien joukkoa. 52 prosenttia tehtäväpalautuksista oli oikein, 17 prosenttia väärinkäsityksiä ja loput 31 prosenttia voidaan selittää loogisesti. 95 prosentilla niistä palautuksista, jotka luokiteltiin väärinkäsitykseksi, oli useampi yhtä hyvä selitys, kun keon koko oli 10. Työ esittää Python-ohjelman, joka voi automaattisesti luokitella tunnettuja väärinkäsityksiä. Työ esittää myös teoriaa, kuinka tuottaa VAS-tehtävien lähtödataa siten, että se tukisi väärinkäsitysten tunnistamista. Teoriaa on sovellettu parantam alla Dijkstran algoritmi -tehtävän syötteen tuottamista. Johtopäätöksenä OpenDSA:n VAS-tehtävien väärinkäsitysten tutkiminen vaatii nykyisellään tehtäväkohtaista työtä. Kaikki OpenDSA:n VAS-tehtävät eivät tallenna riittävästi dataa myöhempää analyysiä varten. Lisäksi tehtävätoistin ja analyysiohjelma pitää kirjoittaa erikseen joka tehtävälle. On tarve kehittää OpenDSA:n ohjelmakirjastoja tuottamaan yksityiskohtaisia tehtävätallenteita. Binäärikeon rakentaminen -tehtävässä pitäisi tutkia keon koon vaikutusta väärinkäsitysten tunnistamiseen

High-school students' mastery of basic flow-control constructs through the lens of reversibility

High-school students specialising in computing fields need to develop the abstraction skills required to understand and create programs. Novices' difficulties at high-school level, ranging from mastery of the "notional machine"to recognition of a program's purpose, have not been investigated as extensively as at tertiary level. This work explores high-school students' code comprehension by asking to reason about reversing conditional and iteration constructs. A sample of 205 K11 - 13 students from different institutions were asked to engage in a set of "reversibility tasklets". For each code fragment, they need to identify if its computation is reversible and either provide the code to reverse or an example of a value that cannot be reversed. For 4 such items, after extracting the recurrent patterns in students' answers, we have carried out an analysis within the framework of the SOLO taxonomy. Overall, 74% of answers correctly identified if the code was reversible but only 42% could provide the full explanation/code. The rate of relational answers varies from 51% down to 21%, the poorest performance arising for a small array-processing loop (and although 65% of the subjects had correctly identified the loop as reversible). The instruction level did not have a strong impact on performance, indicating such tasks are suitable for K11, when the basic flow-control constructs are usually introduced. In particular, the reversibility concept could be a useful pedagogical instrument both to assess and to help develop students' program comprehension

Development of Computational Thinking in Brazilian Schools with Social and Economic Vulnerability: How to Teach Computer Science Without Machines

Computational Thinking (CT) has been placing the focus of educational innovation as a set of troubleshooting skills. Unfortunately, there is not a consensus if the teaching methodology and the available materials attend the expectations of the lecturers. To prove the impact that CT training has in primary school, we attempted to evaluate primary school students with a Quasi-Experimental approach and taking Unplugged CT classes in Brazilian Schools with Social and Economic Vulnerabilities. The research happened in two schools to prove if the activities are effective for students who live in areas where there are no electronic devices, Internet or even electrical power can be also benefited. The results show statistically significant improvement. Our study finds shows that we are able to reinforce the claim that CS unplugged is an effective approach and it is an alternative for students who live in unprivileged areas

Using an e-learning tool to overcome difficulties in learning object-oriented programming

This study was motivated by the need to overcome the pedagogical hindrances experienced by introductory object-oriented programming students in order to address the high attrition rate evident among novice programmers in distance education. The initial phase of the research process involved exploring a variety of alternative visual programming environments for novices. Thereafter the selection process detailed several requirements that would define the ideal choice of the most appropriate tool. An educational tool Raptor was selected. Lastly, the core focus of this mixed method research was to evaluate undergraduate UNISA students’ perceptions of the Raptor e-learning tools with respect to the perceived effectiveness in enhancing novices’ learning experience, in an attempt to lower the barriers to object-oriented programming. Students’ perceptions collectively of the Raptor visual tool were positive and despite the fact that the sample size was too small to achieve statistical significance, these quantitative and qualitative results provide the practical basis for implementing Raptor in future. Thus providing learning opportunities suited to learner interests and needs, can lead to an enormous potential to stimulate individuals’ motivation and development in creating a more positive learning experience to overcome barriers in programming and enhance concept understanding to address the diverse needs of students in distance education that could lead to a reduced dropout rate.ComputingM. Sc. (Computing

KNITTING CODE: EXAMINING THE RELATIONSHIP BETWEEN KNITTING AND COMPUTATIONAL THINKING SKILLS USING THE NEXUS OF PRACTICE

Due to the rise of careers in STEM-related fields, there is a growing need for schools to produce people to fill these positions. One area of STEM that is growing is computer science/coding. Due to this demand, schools need to be intentional about exposing students to computer science/coding. There are a variety of new tools to introduce students to this field. One growing belief is that knitting can teach computer science/coding to students. The goal of this study was to see if knitting can serve as an introduction to teach students computation skills. Kitting has historically been used to code information, and numerous statements have been made that knitting can teach computer coding. The rationale behind this thought is that both fields have similar components and can serve to make coding more accessible to a broader audience. Suppose students that generally would not identify with computer science/coding due to perceived social norms develop an interest in knitting. In that case, they could use what they learned as a foundation to develop an interest in computer coding. This is based on Scollon\u27s Nexus of Practice (2001), which studies how practices are linked together. This theory believes that combining different practices makes a possible crossover from one practice to another. As a result, what may not have been accessible at first due to biases or identity, may become more accessible. This study will focus on whether knitting can teach students computational skills and change students’ identity towards computer science/coding. There is limited research on the relationship between knitting and coding. This case study attempted to determine if knitting could teach coding. The research was conducted during two three-week summer enrichment programs. Results revealed that teaching computer coding through knitting was comparable to traditional instruction. While not necessarily better, this shows that knitting can teach computation skills and improve identity. This could be important for encouraging students that would not typically study computer science/coding to enter the field

A review and assessment of novice learning tools for problem solving and program development

There is a great demand for the development of novice learning tools to supplement classroom instruction in the areas of problem solving and program development. Research in the area of pedagogy, the psychology of programming, human-computer interaction, and cognition have provided valuable input to the development of new methodologies, paradigms, programming languages, and novice learning tools to answer this demand. Based on the cognitive needs of novices, it is possible to postulate a set of characteristics that should comprise the components an effective novice-learning tool. This thesis will discover these characteristics and provide recommendations for the development of new learning tools. This will be accomplished with a review of the challenges that novices face, an in-depth discussion on modem learning tools and the challenges that they address, and the identification and discussion of the vital characteristics that constitute an effective learning tool based on these tools and personal ideas