Khan Academy

Research Proposal for Khan Academy
Name
Institution

Research Proposal for Khan Academy
Data Collection
This research study purposes to determine the effectiveness of Khan Academy as a teaching and instruction approach with the focus being on mathematics learning. A descriptive-correlational research design will be applied to accomplish this objective. The choice of research design is guided by the research objectives. The selected research methodology makes it possible to record and appraise the hypotheses and variables being scrutinized (Martella, Nelson & Morgan, 2013). The variables, both the dependent and independent variables, are not to be altered even if new influences that may cause variation are presented. Of particular interest is how the education approaches affect student outcomes in standard tests (Bernard, 2011).
Data collection will be conducted in two stages. The first stage is the secondary information collection that entailed perusing relevant peer-reviewed literature and presentation that information they contain and which is considered relevant to the topic presented for the research. This phase will be accomplished by collecting information sources from publications to include documents, articles, books and online databases. In addition, search engines would be used to collect information by focusing on key words, phrases and terms that can be linked to the research topic. The information collected from the secondary sources would then be used to establish the literature review, which presents information in relation to the research intentions (Whitley, Kite & Adams, 2012).

The second stage will involve primary data being acquired by applying a mixed methodology approach that includes elements from both qualitative and quantitative research approaches. The quantitative element will entail applying an experimental approach whereby the population sample is exposed to different conditions (Khan Academy method versus other teaching methods) and the variances in teaching methods assumed to explain the differences note for the learning opinions, perceptions and outcomes. This will include subjecting the students to standardized tests before and after the teaching approaches were applied with the performance in the tests noted as the result of the teaching approach that the student was exposed to. The qualitative aspects of the research will entail the use of surveys and interviews. This will be applied to appraise the participants’ both before, during and after exposure to the two teaching approaches as contrasts (Cohen, Manion & Morrison, 2013).
The research purpose is to validate the decision to apply a specific teaching method. It acknowledges that the range of teaching methods are applied for cost and convenience purposes (Yanow & Schwartz-Shea, 2015). On the other hand, the research objective is to evaluate the two learning methods and identify the best method. In that sense, the research will apply positivist paradigm whereby it strives to ascertain that single reality in that the researcher and participants are independent, and the survey procedure would offer a value-free methodology for establishing the truth that one method is better than the other method (Babbie & Benaquisto, 2009).
Quantitative research emphasizes deductive reasoning that shifts from a common idea to a more specific idea. Outcomes validity is dependent on one or more arguments holding such that having an erroneous basis of argument makes it inaccurate. The proposed research is more concerned with making accurate inferences than having access to all members of a study population. It is, therefore, vital that all the participants engaged in the study are an illustration of the study population (Bernard, 2011). Additionally, inferences are validated by the number of participants engaged in the research, how they were chosen, and whether they are illustrative of the population. In essence, making insinuations and extrapolations from the results is not partial to the participants but also to circumstances such that the outcomes reveal the accurate state that the research seeks to clarify and answers the research questions (Babbie & Benaquisto, 2009).
This study is grounded on the fundamental theoretical supposition that a particular method would offer useable research. In fact, it intones that a consolidation of quantitative and qualitative methodologies is suitable for evolving the research knowledge. This is based on the awareness that carrying out and assessing the research includes assumptions. The proposed research method is an interpretive and descriptive case study that will be evaluated through both qualitative and quantitative methodologies (Cohen, Manion & Morrison, 2013).
In essence, the research will use an integrated research approach as the foundation for gathering primary information. The selected approach emphasizes deductive thinking that moves from the common to specific. The primary information will be acquired from completed standardized test results and questionnaires. The research approach will entail exposing the participants to the data collection tools (questionnaires and standardized tests) after receiving their consent. The acquired information would then be exposed to scrutiny by statistical software to highlight significant features (Martella, Nelson & Morgan, 2013). The research recognizes that it does not have access to all students, as such it will only deal with making extrapolations about learners in general. Consequently, it is considered important that the participants engaged in the research be an illustrative example of the broader learners groupings. Conversely, it acknowledges that the extent to which generalities can be made is dependent on the sample size, selection strategies and demographic representation (Whitley, Kite & Adams, 2012).
The research will apply purposive sampling that seeks to set definite standards that participants have to observe for inclusion in the study. The set inclusion standards required that the members of the research group be students who use Khan academy in their mathematics instruction while the students in the control group are those who use other methods apart from Khan academy approach. They would then be chosen based on their consent (Bryman & Bell, 2015).
It is evident that the research intends to apply both inductive and deductive methods. The inductive method entails the research making precise annotations from the amassed information to arrive at a new theory. On the other hand, the deductive method entails collecting and reviewing theories that are then tested using tangible data. Since the two methods are not exclusive, elements from both methods will be applied (Bernard, 2011). Supporting theories using case studies is a widely accepted research approach that comprises recursive cycling in the pertinent literature, emerging theories, and case data. A plurality of cases is used to generate theoretical propositions and constructs from evidence based on the cases. The analytical generalization logic is reinforced through theoretical replication logic (Yanow & Schwartz-Shea, 2015).
It is anticipated that four principal themes will emerge from the collected data. The first anticipated theme is that Khan Academy will allow its students to have a better understanding of mathematics thereby presenting higher confidence levels to be revealed through the surveys and interviews. Secondly, Khan Academy students will perform better than their counterparts who use the normal instruction method to indicate that they are more knowledgeable. This will be revealed by a review of the test scores where Khan Academy students are expected show greater improvement in mathematics when compared to other students. Thirdly, it is anticipated that spending more time using Khan Academy will be accompanied by greater mathematics knowledge such that student who has spent more time using Khan will perform better than their counterparts who have spent less time using the instruction method. Finally, teachers and instructors are anticipated to show greater confidence in Khan Academy’s capacity to produce better-performing students. Once data has been collected, their themes will be tested and ascertained in the data analysis as shown the triangulation table (see Table 1).
Table SEQ Table * ARABIC 1. Data triangulation chart
Source 1 Source 2 Source 3 Source 4
Test results (before, during and after) Questionnaires Interviews Tables and charts of percentages for the test, questionnaire and interview results
Outcome Interpretation Events that precipitate the outcome:
Maintaining the desired outcome:
Functions that support the desired outcome:
Data Analysis
The collected quantitative data will be analyzed and offered using SPSS statistical analysis software. This is based on the awareness that data analysis is the effort surrounding data collection and presentation of results in a format that points out valuable evidence that can be applied in decision-making practices. The use of statistical software aids in determining data relevant codes and their presentation in a suitable format as the inferences to be made in the study will be grounded on the acquired information, thereby requiring correct data analyses that point out the relevant data feature. Choosing the statistical software to be applied in the analyses of data is dependent on the need to aggregate and decode the acquired primary data. As raw primary information, the collected data from participants and respondents is bulky and takes much resources and time to evaluate (Yanow & Schwartz-Shea, 2015).
The carefully chosen statistical software is expected to carry out the evaluation and execute an exhibition based on a range of commands. In general, the software carries out four key activities when evaluating the raw primary information to include reading, transforming, defining variables, creating tables. Reading the primary data entails converting the raw information into a format that can easily be read by the software. Data transformation comprises activities to guarantee that the data is assigned in the correct way. Variables definition allocates tags while creating table offers the information in a coalesced format that can comprehend very easily (Bryman & Bell, 2015).
Regarding the collected qualitative data from interviews, data analysis will be conducted dependent on the need to aggregate and decode the data. As raw data, the interview results are cumbrous and take much resources and time to analyze. This will be achieved by determining the emerging themes within the data to entail inductively ascertaining codes contained in the collected data, shaping the revealed codes into themes, arranging the themes into sets centered on acknowledged configurations, dissecting the sorted information to segregate the configurations, and lastly reflecting on the configurations to generalize the information for the population (Robson, 2007).
Overall, data analysis will adopt seven principal strategies. The first strategy is information batch totals check that entails perusing the collected information to identify missing data fields that would then be added. The second strategy is information consistency checks, which involves scanning the collected information to guarantee that all the fields have the suitable matching information input. The third strategy entails checking information cross-system consistency, which involves comparing information across diverse structures to guarantee that they tally. The fourth strategy is checking the data type checks to guarantee that each information field has the correct type of information. The fifth strategy is data control totals checks, which refer to the summations done in the numeric fields. The sixth strategy is table lookup checks, aimed at ensuring that information provided in the tables are valid when matched to information found in connected tables. The final strategy is referential integrity checks are to guarantee that all the figures and tables comprise diverse forms of the same information (Whitley, Kite & Adams, 2012). The mentioned actions describe the data analysis process to be adopted by the research when handling both the qualitative and quantitative data.

References
Babbie, E, & Benaquisto, L. (2009). Fundamentals of Social Research, Washington, DC: Education Publishers.
Bernard, R. (2011). Research Methods in Anthropology: Qualitative and quantitative approaches (5th ed.). Lanham, MD: AltaMira Press.
Bryman, A. & Bell, E. (2015). Business Research Methods (4th ed.). Oxford: Oxford University Press.
Cohen, L., Manion, L. & Morrison, K. (2013). Research Methods in Education. New York, NY: Routledge.
Martella, R., Nelson, R. & Morgan, R. (2013). Understanding and Interpreting Educational Research. New York, NY: The Guilford Press.
Robson, C. (2007). How to do a Research Project: A guide for undergraduate students. Oxford: Blackwell Publishers.
Whitley, B., Kite, M. & Adams, H. (2012). Principles of Research in Behavioral Science (3rd ed.). New York, NY: Routledge.
Yanow, D. & Schwartz-Shea, P. (2015). Interpretation and Method: Empirical research methods and the interpretive turn (2nd ed.). New York, NY: Routledge.