Many parents and caregivers are adopting home reading as a tool for helping children develop literacy skills as well as acquire particular languages. Consequently, there is a need to establish the roles played by home reading in promoting children’s literacy development (Burchinal, Roberts, Riggins, Zeisel, Neebe & Bryant, 2000). The upcoming study’s objective will be two-fold. First, it shall seek to examine the efforts made by home readers to support, or promote, children’s literacy development and acquisition of particular languages. Second, the study shall seek to examine the factors that are considerably linked to enhanced language promotion, as well as increased literacy, in home reading programs. The research study’s methodology along with design shall be suitable for supporting the seeking of answers to these questions:
- What is the degree to which home readers engage young persons in literacy along with language activities within home settings?
- What home reader attributes are considerably linked to enhanced language promotion, as well as increased literacy, in home reading programs?
Research designs are aimed at making certain that the evidence got in research studies enables researchers to efficiently deal with the related research problems as explicitly and logically as possible (Festinger, DeMatteo, DeMatteo & Marczyk, 2013). The designs help specify the categories, or groups, of data that need to be gathered, the groups targeted by particular interventions, and the proper timelines for gathering particular data. A research design’s strengths and probable inherent biases are dependent on the questions that are being addressed in the research (Creswell, 2014).
As noted earlier, the questions to be addressed in the upcoming study are “What is the degree to which home readers engage young persons in literacy along with language activities within home settings?” and “What home reader attributes are considerably linked to enhanced language promotion, as well as increased literacy, in home reading programs?” These questions are causal in their nature. Consequently, a causal research design shall be adopted for the upcoming study.
Why The Causal Design Will Be The Most Suitable For The Upcoming Study
A causal design will be the most appropriate design for the study. Causal studies entail the appreciation of given phenomena based on statements that in themselves conditional, especially in the “if this, then that” form. The studies focus on measuring the effects of particular changes on the extant assumptions along with norms. Commonly, in social sciences, researchers are keen on establishing causal explanations reflecting hypothesis tests. Causal effects, from a nomothetic viewpoint, happen when variations in given phenomena represented by independent variables, causes variations in particular phenomena represented by dependent variables.
The aforementioned questions present the upcoming study as motivated by the need to determine causality. The study will especially be hinged on the need to find empirical connections between different phenomena, some represented by dependent variables and the rest represented by independent ones. The causal design is particularly appropriate for answering the aforementioned questions for several reasons. First, the expected outcomes in e each of the questions will be measured in a group that will have been taken through particular interventions along with a comparable group that will not have been taken through the interventions. Second, repeated outcome measures will be executed severally prior to and following the application of particular interventions to the test group envisaged in each of the questions (Creswell, 2014).
Notably, the upcoming study will be capable of fulfilling the conditions necessary for establishing causal effects between phenomena via research. The effects are only established where there is suitable time order. That means that a researcher can only validly conclude that causation is involved after seeing that given cases were rendered to independent variable variations prior to dependent variable variations (Creswell, 2014). As well, causal effects between phenomena can only be determined where the two sets of variables do not have a spurious linkage, the connection between them should be stemming from another variable’s variation.
If the causal design is adopted for the upcoming study, it will help the researcher to appreciate why or why not home reading impacts on early emergent literacy skill as well as language acquisition via the establishment of a causal connection between particular variables and elimination of other possibilities (Kothari, 2005; Bellamy, 2011). If the causal design is adopted for the upcoming study, replication, or generalization, of the outcomes will be possible. As well, the study will be defined by a high degree of confidence since it will have internal validity owing to the related systematic selection of subjects and the equity of the subject samples that will be compared.
Why Other Designs Will Not Be As Inappropriate As Causal Design
Since the upcoming study will be based on the need to prove causal connections between given variables objectively, an action research design (ARD) will be inappropriate. That is because ARD entails the over-involvement of researchers in the studies they are executing, increasing the possibility of bias, non-objectivity, in the resulting outcomes (Festinger, DeMatteo, DeMatteo & Marczyk, 2013). As well, the ARD’s cyclic character will present challenges to the researcher since its twin research and action outcomes are intricate and time-consuming to conduct.
A case study design (CSD) will be unsuitable for the upcoming study since it involves a limited number of subjects, or cases, or even single cases. The number of subjects, or cases, presents a shaky and rather limited foundation for generalizing a study’s findings to broader populations. The number also presents marked challenges in establishing the findings’ reliability. Indeed, CSD will be inappropriate for the upcoming study since one cannot use it to assess “if this, then that” relationships.
The cohort design is markedly flexible and preferred when one is keen on gaining insight into particular effects, or outcomes, over time. When one adopts the design for a particular research, he or she can use secondary or primary data. Notwithstanding these two strengths that would have made the design appropriate for the forthcoming study, it is not as suitable for the study as the causal design for several reasons (Kothari, 2005; Bellamy, 2011). First, cohort studies determine possible causes prior to the happening of the related outcomes, thus demonstrating that the causes came before the outcomes. Consequently, cohort studies do not explicitly define a cause and the related effect. Second, in cases where multiple cohorts are analyzed comparatively, researchers are unable to control for every factor, or confounding variable, differing among the cohorts.
When the cross-sectional design (C-SD) is adopted in a study, it helps provide comprehensible outcome snapshots and the snapshots of the corresponding attributes at particular times. The C-SD helps in the estimation of given outcomes’ prevalence. Even then, the design is inappropriate for the upcoming study since it gives rise to time-bound and static results, which are incapable of indicating the related events’ sequences and temporal or historical contexts (Creswell, 2014). Indeed, the application of the C-SD is incapable of conclusively determining “if this, then that” relationships as will ne required in the forthcoming study to establish home reading’s impact on children’s literacy skills as well as language acquisition.
A descriptive design will be unsuitable for the upcoming study since it gives rise to results that have no utility with respect to disproving or proving given hypotheses definitively. Besides, the results are not widely generalisable, or replicable. An experimental design will be unsuitable for the upcoming study since although it allows researcher identify causal connections, it is artificial (Laurel, 2003; Vogt, Gardner & Haeffele, 2012). Consequently, the related results are not widely generalisable to the actual world. An exploratory design will be unsuitable for the upcoming study since it supports the usage of only samples with limited sizes. That means the related results are characteristically not widely generalisable.
A historical design will be unsuitable for the upcoming study since it supports researches that depend on historical, or past, data without allowing for its manipulation to control, or regulate, for present contexts (Festinger, DeMatteo, DeMatteo & Marczyk, 2013). A longitudinal design will be unsuitable for the upcoming study since its presents marked challenges in the maintenance of sample integrity over long periods. It will be unsuitable regardless of the actuality that it allows researchers get causal explanations the way they would through the execution of experiments.
A meta-analysis (MA) design will be unsuitable for the upcoming study since even rather limited violations in characterizing the related content analysis criteria may result into difficulties in the interpretation of the attendant outcomes. In some cases, the violations lead to meaningless outcomes (Kothari, 2005; Bellamy, 2011). As well, in MA studies, even though large subject samples can give rise to reliable outcomes, the outcomes are nor inevitably valid.
An observational design will be unsuitable for the upcoming study since it the reliability of observational data is low owing to the difficulties in seeing given behaviors keep recurring. The results got from observational studies are not widely generalisable, or replicable. A philosophical will be unsuitable for the upcoming study since philosophical studies have constrained application to particular research problems, including the ones requiring the establishment of causal relationships (Creswell, 2014). As well, philosophical analyses may be limited, argumentative, and abstract in its matter-of-fact application to actual issues.
Besides, a sequential design will be unsuitable for the upcoming study since it does not allow for randomized subject sampling (Festinger, DeMatteo, DeMatteo & Marczyk, 2013). That means that sequential studies contain no interpretations and conclusions pertaining to whole populations, limiting their finding’s generalizability. In addition, in sequential studies, there are marked challenges in accounting for, as well as interpreting, variations between given samples over long periods.
In some cases, research studies entail the whole populations of interest. However, more commonly they involve only limited portions of the analysis units. Typically, sampling reduces the time, as well as costs, needed to execute given researches. Sampling enhances the quality of the gathered data, or information, since it allows for rather intensive gathering of data (Festinger, DeMatteo, DeMatteo & Marczyk, 2013). Besides, sampling lessens the obligations, or burdens, on research study respondents. For the upcoming study aimed at examining the efforts made by home readers to support, or promote, children’s literacy development and acquisition of particular languages and examining the factors that are considerably linked to enhanced language promotion, as well as increased literacy, in home reading programs, a stratified sampling method (SSM) will be adopted. Specifically, a matched subject sampling approach (MSSA) will be adopted. Notably, MSSA is one of the forms taken by SSM.
In stratified sampling, populations are taken as embracing diverse distinct classes, which are used in organizing research frames. In the upcoming study, one of the populations of interest will be that of home readers, those taking children through home reading sessions to acquire language, as well as literacy skills (Creswell, 2014). The other population of interest will be that of the teachers who exclusively teach children to attain literacy skills along with language.
Unlike other sampling approaches, the MSSA will be appropriate for the upcoming study since it will allow for the emulation of the within-subject design (WSD) conditions of the subjects while steering clear of the sequential effects that may impact on the attendant results. WSDs test same groups of individuals whereas the MSSA comes quite close to that; even using similar statistical techniques in result analyses. The MSSA eliminates the likelihood of variations between subjects impacting on results. Besides, the approach uses the distinct strengths of the BSD (between-subjects design). Each subject in a study gets tested once, preventing the likelihood of order effects, or temporal factors, impacting on the resulting outcomes.
Unlike all the non-stratified sampling methods, the MSSA will allow the researcher to divide the relevant populations into independent and distinct, strata. The researcher will be capable of drawing inferences regarding particular subgroups that may not be considered in random samples that are rather broadly generalized (Kothari, 2005; Bellamy, 2011). Unlike all the non-stratified sampling methods, the MSSA will allow the researcher to get rather effective statistical estimates if the selection of the strata of interest will be hinged on the corresponding criterion as opposed to sample availability. Notably, even where stratified sampling fails to heighten statistical efficacy, the default efficacy is always more than the one resulting from simple random sampling if every stratum is relatively proportional to the size of the corresponding subject group.
Generally, the MSSA and all SSM approaches in general are best suited for the upcoming study since they focus on essential subpopulations, ignoring the ones that are irrelevant. The MSSA and all SSM approaches in general allow for the utilization of diverse sampling approaches for diverse subpopulations. The MSSA and all SSM approaches in general enhance the efficiency or accuracy of estimation (Laurel, 2003; Vogt, Gardner & Haeffele, 2012). Lastly, the MSSA and all SSM approaches in general allow for enhanced balancing of difference test statistical power between given subject strata by sampling the same number of subjects from each stratum regardless of its size in relation to the others.
The forthcoming study will be quantitative in nature. In quantitative studies, researchers develop the majority of own research questions, as well as hypotheses, quite particularly prior to executing the studies (Festinger, DeMatteo, DeMatteo & Marczyk, 2013). Thereafter, they develop or find suitable tools, or instruments for gathering the requisite data. The researchers get opportunities for refining every item. Even then, they get no chance for addressing questions that may emerge during the early phases of data collection.
In quantitative studies, there are two principle elements relating to the gathering of the requisite data: procedures for gathering the data and the corresponding instruments. In the upcoming study, the requisite data will be gathered via sample surveys. The respondents will be issued with survey forms containing diverse questions (Creswell, 2014). They will be informed that their participation in the survey will be stringently confidential and voluntary. In the forms, the respondents will provide details of themselves as childhood educators. The details will relate to their demographic variables: household income, number of years spent as childhood educators, gender, ethnicity, education level, and age.
The respondents will also provide details on their experiences instructing children to gain elementary literacy skills on the survey forms, or questionnaires. Two universal items will be developed to determine the experiences. The items will seek to establish whether or not a respondent has gotten sufficient professional training to teach young ones to read. The other one will seek to establish whether or not the respondent feels that he or she gotten sufficient professional training to teach young ones to read. The respondents will be provided the choice of indicating “No” or “Yes” with respect to each of the two items. The respondents will provide information on program attributes on the questionnaires. The attributes include the type of settings in which they teach children, whether or not the settings have sufficient print materials, and the number of children they teach to read.
An instrument comprising of 23 items for determining the level to which the respondents promote literacy, as well as language, activities in their settings will be developed. The items will be geared towards establishing how often the respondents engage children in the different activities. Each of the items will have five response options, ranging from “at all times” (5) to “not at all” (1). Notably the items will focus on particular instructional approaches linked to the facilitation of young learner’s emergent literacy competencies, including the extant child-instructor reading practices, book-related instruction, exposure to reading materials, and letter and word recognition along with support for phonological awareness. It is expected that the scale comprising of 23 items will show outstanding internal reliability when put together to form a lone measure for literacy, as well as language, promotion.
Notably, other data collection methods will not be as suitable for the study as the survey method. It will be impractical to use the census method owing to the related practicality, time, and cost implications. An experimental method will be unsuitable since the experimental design is artificial (Creswell, 2014). Consequently, the related results are not widely generalisable to the actual world. The observational method will be unsuitable since the reliability of observational data is low owing to the difficulties in seeing given behaviors recurring. The survey method will be rather suitable since the population is expected to be large, the outcomes will be easily generalisable, and allows for causal inference.
The respondent answers relating to “what is the degree to which home readers engage young persons in literacy along with language activities within home settings?” will have their frequencies run on the respondents’ answers to each of the items. The response classes will be collapsed into “sometimes”, “often”, and “seldom” categories. After the categorization of the responses in the three classes, mean scores will be calculated from the scale. The scores will be representing the extent to which the different sets of instructors make concerted efforts to engage children in literacy as well as language, activities (Creswell, 2014)..
With respect to the respondent answers to “what home reader attributes are considerably linked to enhanced language promotion, as well as increased literacy, in home reading programs?”, the household income, number of years spent as childhood educators, ethnicity, take on literacy training adequacy, number of learners attended to, print material available education level, and received literary training independent variables will be entered into a multiple regression expression, or equation. The variables will be analyzed with the instructors’ efforts towards the promotion of literacy, as well as language, activities being the corresponding dependent variable. This analytical method will be suitable for establishing causal connections in the data that will be gathered.
Research designs are aimed at making certain that the evidence got in research studies enables researchers to efficiently deal with the related research problems as explicitly and logically as possible. A causal design will be the most appropriate design for the forthcoming study. A MSSA will be adopted. Notably, MSSA is one of the forms taken by SSM. The requisite data will be gathered via sample surveys.
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