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Instructional Theories Learning Development

An instructional theory refers to a theory that provides clear guidance on how to assist individuals learn and develop. Instructional theories center on how to design material for enhancing the education of individuals. They differ from learning theories in the sense that while learning theories explain how learning occurs, instructional theories stipulate how to assist individuals to learn.

Stated differently, instructional theories, as informed by learning theories, delineate the core teaching approaches (such as worked examples versus partial solutions, lecture versus cooperative activities, immediate versus deferred reinforcements) that may be included in a lesson. Instructional theories are usually normative and situation specific. The field of instructional science deals with understanding and improving instructional methods to make them more appealing and effective (Edgar, 2012, p. 2).

The origins of instructional theories can be traced to formative endeavors by educational psychologists to map out the link between psychology and the pragmatic application of instructional theory in education settings. John Dewey (1910) and Edward Thorndike (1913) are two important theorists who envisaged a special connection between instructional theory and educational practice (Dijkstra, Schott, Tennyson & Seel, 2012, p. 3). The connection between the philosophical perspectives and instructional theories is obvious. For instance, learning activities in a traditional classroom are centered on and controlled by the instructor, who presents the materials to be learned and prescribes the kinds of learning activities that students engage in.

Learners are expected to read and analyze the information (through homework and classroom activity) until they master it. Knowledge is regarded as a commodity to be passed from the teacher to the learner. In sum, instructional theories identify methods of instruction (ways of supporting and facilitating learning), as well as the circumstances in which the methods may or may not be used.

A Perspective on the Connection between Theory and Practice

The connection between instructional theories and pedagogical practices is made complex by a number of factors. It can be perceived that pedagogical practices should be founded on the best instructional theories available, but this relationship may not be as simple. Educational practices are likely to be informed by philosophical beliefs than by empirical evidence and theoretical discernment of learning. Learning institutions are established according to the various cultural and community beliefs and worldviews, the human nature, as well as what are to be learned. They also differ with respect to their beliefs regarding teaching and learning, although philosophical convictions frequently come first (Duffy & Jonassen, 2013, p. 17).

All instructional programs and educational systems incorporate some instructional theory, even though such theory is in most instances implied and frequently goes unnoticed. Vastly different classrooms materialize from different philosophical views. For instance, if one is of the conviction that knowledge is produced anew by each student, that a student’s mental activity decides what he or she learns, and that learning happens from engaging in authentic assignments in a social atmosphere, then the resultant classroom is likely to involve learners working on projects and learning in groups.

In this manner, the students are able to discuss how best to tackle problems or consult on the meaning of various concepts. There is a consistency between theoretical beliefs and pedagogical practices. However, the question concerning which comes first is not always clear since evidence exists that people seek out and agree to information that affirms their preexisting beliefs while rejecting those that do not conform to such beliefs.

There exists a reciprocatory link between theory and practice. A common conviction is that knowledge flows from systematic theories to the advancement of effectual practices, that effective instructional theories inform sound pedagogical practices (Leong & Austin, 2006, p. 7). However, science does not always work in such a linear manner. An examination of both social and physical sciences reveals that ideas frequently derive from observation and interrogation of naturally occurring events. Scientific theories often come from attempts to find practical solutions to problems, such as asking the question “what is the best approach of teaching the concept of osmosis?”.

Established pedagogical practices that teachers have been found to be effectual should be used as sources of ideas in coming up with a practicable instructional theory. A final caveat in comprehending the connection between theory and practice involves acknowledging that the learners are more important than the instructor in deciding the material to be learned. However, this is not to say that the teacher’s role is unimportant, only that the perceptions, previous knowledge, and beliefs of learners should dictate what and if they learn things related to the teacher’s instructional goals.

Attribution Theory

This theory deals with the manner in which individuals perceive and use information to explain events (Higgins & LaPointe, 2012, p. 1). It looks at what information is collected and how it is treated to shape a causal judgment. Heider (1958) first proposed the attribution theory, although other psychologists such as Weiner (1974) and Jones et al (1972) developed a theoretical framework that later became a key research model in social psychology. Heider offered a discourse on what he termed as “commonsense” or “naïve” psychology. According to his perspective, individuals are similar to recreational scientists, attempting to understand the behavior of other individuals by gathering and analyzing information until they obtain a reasonable cause or explanation.

Instructional Theories – Key Statements and Assumptions

Attribution theory concerns itself with how people construe events and how this construal relates to their thoughts and behaviors. The theory presumes that individuals try to determine why people behave in the manner that they do. An individual seeking to understand why other people or person behaved in a certain manner may attribute one or several causes to the behavior (Erbas, Turan, Aslan & Dunlap, 2010, p. 118). Heider proposed that individuals usually make two kinds of attributions, namely internal attribution and external attribution.

Internal attribution involves the deduction that a person is acting in a certain manner because of some inherent attribute about the individual, such as personality or attitude. Conversely, external attribution involves the assumption that a person behaves in a certain manner due to the circumstances that he or she is undergoing. Attributions are also considerably affected by motivational and emotional drives (Higgins & LaPointe, 2012, p. 3). Faulting other people and evading personal blame are existent convenient and self-serving attributions.

Instructional-Theories-Learning-Development
Instructional-Theories-Learning-Development

Individuals also tend to make attributions in defending against what they perceive as attacks. People sometimes even blame victims for their circumstances as they seek to distance themselves from thoughts and feelings of suffering the same predicament. Lastly, individuals also tend to assign less variableness to other people than themselves, viewing themselves as more versatile and less conventional compared to others.

A three-stage process forms the basis of an attribution. First, the individual must observe or perceive a behavior. Second, the individual must trust that the behavior was deliberately performed, and lastly, the individual must establish if he or she believes that the other person was coerced into performing the behavior (in such a scenario, the cause will be attributed to the circumstances) or not (where the action will be attributed to the other individual). Weiner’s attribution theory focused on achievement. He identified effort, aptitude, task complexity, and luck as essential factors that affect attribution for achievement (Higgins & LaPointe, 2012, p. 2). Attributions are categorized under three underlying dimensions, which include stability, controllability, and the locus of control (Jarvis, 2012, p. 148).

The stability dimension looks at whether causes remain constant or change with time. For example, effort may be categorized as internal and variable while aptitude may be categorized as a constant, internal cause. Conversely, controllability contrasts causes that are within the control of an individual, such as skills, from those that one is not able to control, such as mood, ability, the actions of other individuals, and luck. Lastly, the locus of control dimension is divided into two poles, which include external and internal locus of control.

Application of the Attribution Theory

Weiner’s Attribution Theory has found widespread application in various fields, including clinical psychology, law, and education. Weiner contended that causal attribution determines how people react to achievement and failure. For instance, a student is not likely to experience a sense of pride and accomplishment if he or she receives an A grade from an instructor who gives only higher grades. Conversely, a higher grade from instructors who issues few high grades is likely to lead to immense satisfaction to the student (Weiner, 1980, p. 362).

Students with higher academic achievements and high self-esteem often attribute their superior performance and achievements to internal, established, and intractable factors such as aptitude while attributing failure to internal, tractable factors such as task complexity and the level of effort. For instance, students experiencing recurring failure in numeracy are likely to consider themselves as being less proficient in arithmetic.

This self-perception of numeracy ability evidences itself in the learner’s prospects of success on numeracy tasks, as well in their thoughts on failure or success in the same tasks. Similarly, learners with learning disabilities are more likely to attribute their failure to ability, which is an intractable factor and not effort, which is more tractable.

The Elaboration Theory

This theory holds that to optimize learning, instruction should be prepared in an order of increasing complexity. For instance, when teaching procedural tasks, it is important to present the simplest adaptation of the task first. The lessons that follow should present additional adaptations until all the tasks have been taught. In all the lessons, the teacher should remind the students of all tasks taught (synthesis or summary). An important view of the Elaboration Theory is the observation that the student needs to develop a purposeful context for the assimilation of consequent skills and ideas (Nenkov, Haws & Kim, 2014, p. 769). Therefore, the Theory deals solely with organizational approaches at the macro level.

It stipulates that the instruction begin with an overview that provides knowledge of a few simple but general ideas, with the rest of the instruction presenting exhaustive ideas that expound on earlier ones. The Elaboration Theory includes three models of instruction, as well as systems from stipulating these models based on instructional goals.

Similar to other models of instruction, the three components comprise strategy components. It is imperative to note that the Elaboration Theory is not fixed, but continues to improve as studies expose weak strategy aspects that should be purged from the model and novel strategy aspects that ought to be included into the models.

The Models of the Theory

The three models of the elaboration include procedurally organized model, the conceptually organized model, as well as the theoretically organized model (Reigeluth, 2013, p. 368). A procedurally organized learning program, such as a regression analysis course, would teach the least complex and most generally applicable processes and procedures first, with the rest being taught as is necessary in attaining the same purpose but under different and more challenging conditions.

Conversely, a course in genetics may utilize a conceptually organized model where the general concepts are presented first. Lastly, a course in introductory microeconomics would probably utilize a theoretical structure where the fundamental principles (such as marginal costs, costs and opportunity costs, scarcity, rational choices, etc.) are taught first.

Application of the Elaboration Theory

The theory may be applied to the design of instruction, particularly in the cognitive domain. Instruction is more effectual when it adheres to an elaboration strategy, that is, the use of epitomes comprising analogies, motivators, syntheses, as well as summaries. For instance, nearly all economic principles may be explained as elaborations of the classic law of demand and supply, including taxation, regulation, and monopolies.

Problems with the Instructional Theories and Recommendations

Elaboration theory contends that the structure of content should be made plain and overt to learners through a number of organizers and synthesizers. This view is rather problematic in the sense that presenting learners with an outline that reflects the text structure is likely to encourage memory-level indoctrination and encumber the transfer of the memorized material to problem-solving assignments. Such likely negative outcomes of explicit teaching structure might be because of the continuous knowledge-of-result feedback that is usually characteristic of motor learning tasks. It is uncontested that learning may not occur when learners are able to decipher things effortlessly.

As it is currently constituted, the Elaboration Theory is more of an instructional design procedure than a theory. It provides precise steps for structuring instruction. Such a procedural approach presents two principal problems. First, the procedural directions prescribed beforehand often go beyond the knowledge base regarding instructional and learning processes and are frequently at variance with such knowledge and second, those tasked with designing instructions are disposed to adhere to models in a general, principle-based manner notwithstanding the procedural stipulations.

The theory should be redeveloped into a series of guiding rules that are lucidly referenced to instructional and learning processes. A rule-based formulation will permit instructional designers to adapt the theoretical constructs to a wider variety of situations.

The Component Display Theory

This theory was developed by David Merrill (1983) and delineates the microelements of instruction, that is, particular ideas and means of teaching them (Reigeluth, 2013, p. 279). The theory categorizes learning as bi-directional and comprising of content (concepts, facts, processes, principles, and procedures) and performance (memory and generalities). It identifies four principal forms of presentation, which include rules, examples, recall, and practice.

Rules refer to expositive presentation of generality while examples are expositive presentation of occasions and instances (Duncan & Goddard, 2011, p. 80). Conversely, recall is inquisitory or probing generality while practice refers to probing instances. The Component Display Theory also includes secondary presentation forms, which include goals, mnemonics, preconditions, as well as feedback. The theory stipulates that instruction is only effective as long as it contains all essential primary and secondary forms. Therefore, a comprehensive lesson would comprise of a goal, followed by a permutation of rules, examples, practice, mnemonics, recall, and feedback that are task-specific and appropriate.

CDT further proposes that for a given goal and student, there exists a distinctive combination of the various forms of presentation that leads to the most effectual and successful learning experience. In addition, a number of assumptions underlie the Component Display Theory. While there are several varieties of memory, the theory holds that algorithmic and associative memory structures have direct connections to the performance aspects of Find/Use and remember correspondingly. While algorithmic memory is made up of outlines or rules, associative memory consists of successive levels of network structure. The differentiation between the Find and Use performances lies in the use of extant rules in processing inputs compared to forming new rules through the restructuring of existing ones.

Application of the CDT

 The Component Display Theory has found extensive usage in applied instructional design. It was employed in designing the TICCIT computer-based instructional system (Choi, 1986, p. 40). One of the key roles of instruction is to foster active mental processing by the learner. Evidence exists that there is a direct correlation between the quality and quantity of learning and cognitive processing of pertinent information by the student. Nonetheless, proper use of attention focusing information, as well as an experiential environment, may improve the requisite mental processing, thereby improving the level of learning. Because computers are interactive, the execution of this active involvement becomes easier than is the case with other instructional media.

Limitations of the CDT

There exist at least for different elements of instruction that impinge in student performance, including the organization of instruction, the method of instruction delivery, student motivation, and the method used in managing the interaction between the instruction and the student (Choi, 1986, p. 43). Further, instructional organization may be classified into two distinct categories, which include organizing instruction on a set of topics and organizing it on one topic. The Component Display Theory only examines the organization of instruction on one topic. Although the theory covers only a single, limited facet of instruction, its meticulous procedures offer instructional designers ways of producing effectual instruction within this limited domain.

Instructional Theories Conclusion and Thoughts

The basic aim of instructional theories is to enhance the quality of instruction. A learning-focused instructional theory should provide guidelines for designing learning environments that can offer the proper combinations of self-direction, empowerment, structure, guidance, and challenge. It must also include guidelines for aspects that have been mostly ignored in instructional design, which include deciding among the various instructional approaches, including project-based learning, tutorials, problem-based learning, and simulations.

The needs for learning have increased and, therefore, new paradigms must provide guidelines for promoting social, emotional, spiritual, attitudinal, and ethical development, as well as an intricate understanding, meta-cognitive strategies, complex cognitive tasks, and higher-order critical thinking skills in the cognitive sphere. Various instructional theories must provide guidelines in every of the above spheres of learning and development.

References

Choi, S. Y. (1986). Application of Component Display Theory in Designing and Developing CALI. Calico Journal, 3(4), 40-45.

Dijkstra, S., Schott, F., Tennyson, R. D., & Seel, N. M. (2012). Instructional Design: Volume I: Theory, Research, and Models:volume Ii: Solving Instructional Design Problems. Hoboken, NJ: Taylor and Francis.

Duffy, T. M., & Jonassen, D. H. (2013). Constructivism and the technology of instruction: A conversation. Hillsdale, NJ: Lawrence Erlbaum Associates Publishers.

Duncan, S. F., & Goddard, H. W. (2011). Family life education: Principles and practices for effective outreach. Thousand Oaks, CA: SAGE.

Edgar, D. W. (2012). Learning theories and historical events affecting instructional design in education: Recitation literacy toward extraction literacy practices. Sage Open, 2(4), 1-9.

Erbas, D., Turan, Y., Aslan, Y. G., & Dunlap, G. (2010). Attributions for Problem Behavior as Described by Turkish Teachers of Special Education. Remedial and Special Education, 31(2), 116-125.

Higgins, N. C., & LaPointe, M. R. P. (2012). An individual differences measure of attributions that affect achievement behavior: Factor structure and predictive validity of the academic attributional style questionnaire. Sage Open, 2(4), 1-15.

Jarvis, M. (2012). Teaching psychology 14-19: Issues & techniques. Abingdon, UK: Routledge.

Leong, F. T. L., & Austin, J. T. (2006). The psychology research handbook: A guide for graduate students and research assistants. Thousand Oaks, CA: Sage Publications.

Nenkov, G. Y., Haws, K. L., & Kim, M. J. (2014). Fluency in Future Focus: Optimizing Outcome Elaboration Strategies for Effective Self-Control. Social Psychological and Personality Science, 5(7), 769-776.

Reigeluth, C. M. (2013). Instructional-design theories and models: An Overview of Their Current Status. Hillsdale, NJ: Lawrence Erlbaum Associates.

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Approaches for Research Dissertations

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Approaches for Research Dissertations

Qualitative or Quantitative?

Approaches for all research, whether qualitative or quantitative, requires interpretation and contextualization by the researcher. Narrative statements or a series of figures will not give the answer to the research question or statement (hypothesis) by themselves.

Therefore it is important to choose a research approach (or approaches) that will give the correct ‘type’ of data to answer your research question.

A number of approaches are available when gathering data, but these don’t have to be used in isolation. For instance a focus group can elicit viewpoints which may need exploring further will a larger research cohort using a closed question survey. For this reason, it is important to plan your approach thoroughly before you start, to ensure your research question can be answered and to let your respondees know what is expected of them.

Don’t forget that whichever research method is chosen, it needs to have a robust ethics form that has been approved before contacting participants and starting to gather data.

Approaches that can be used:

Focus groups

This is where a group of people discuss a particular problem, facilitated by the researcher. The group interaction and the sharing of ideas not only means that rich and meaningful data can be pulled out from the focus group but also during the course of the focus groups, ideas can be co-constructed between participants which can be used to further the depth of research.

Structured interviews

When using structured interviews, the questions are written beforehand and are strictly adhered to regardless of the answer.

Semi-structured interviews

Whilst pre written questions are also used in semi structured interviews, this approach allows for the researcher to spontaneously build on answers given, allowing the base question to be answered but also elaborating on any areas which may impact on the research answer.

Survey

Surveys are an excellent way to reach a large number of people. This approach works if there is a clear idea of the questions that will elicit research to support the hypothesis. A mix of qualitative (open text fields) or quantitative (set questions and answers) can be used.

Case study

This approach is valuable when more in depth research is required and allows the researcher to investigate the issues in the place or time that they occur. The researcher will observe the participant and often will have follow up meetings to clarify or build on the information gained.

Narrative enquiry

This method works on the ideology that it is less important what is said, then how it is said. The story a participant will tell may not be entirely factual but it will be their perception of what happened which gives greater in sight. This approach is linked to discourse analysis methodology.

Appreciative enquiry (AI)

AI shifts the traditional focus of looking for the negative impacts of an issue and instead approaches the issue from a positive perspective.

Ethnographic

Ethnographical methodology requires the researcher to embed themselves in the participatory groups own setting, for a sustained time in order to observe, talk and learn from participants.

There are a number of branches from the ethnographic methodology:

Auto ethnographic

More than just an autobiographical account, an auto-ethnographic researcher should reflect on events and use these to uncover meanings and feelings that a purely narrative account may miss.

Visual ethnographic

Using video, photos and artefacts as the main source of research data rather than supplementing it.

Netography

Researchers using this methodology are involved and participants or ‘lurkers’ in virtual groups and communities. Ethical issues need to be carefully considered with this approach.

Soft Systems Methodology (SSM)

Instead of studying isolated issues, SSM is a holistic way of looking at and solving problems. These are often presented in mind map formats, making this a good research methodology for visual learners.

Questions to ask before choosing a research approach:

  1. Will we learn more about this topic using quantitative or qualitative approaches?
  2. Which approach will produce more useful knowledge?
  3. Which will do more good?

References

Taken from:  Cousin. Glynis, (2009) Researching Learning in Higher Education. Routledge. UK.

Research Approaches Dissertations
Research Approaches Dissertations

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Dissertation Research Proposal For University Students

Writing A Research Proposal

This collective article is designed to provide you with a realistic and relevant learning opportunity which will help prepare you for the dissertation. You are asked to prepare a research proposal similar to one that could be submitted to an ethics committee. This proposal could be linked to your proposed dissertation topic, if you have already identified one. If not, it could be associated with a current area of interest. Please see your handbook for information on writing and marking.

You are required to:

  1. Identify a research question/problem
  2. Justify the research, research design and methods
  3. Consider resources & constraints

The main objectives of research ethics committees are to protect both prospective participants in research studies and researchers. To achieve this, ethics committees need specific information regarding proposed studies to be able to make informed decisions about the ethical implications of these studies, considering the proposal from the participants’ perspective. The main ethical issues focus on the validity of the research (is the research question important and do-able?) and the welfare of the participants (what will participation involve, are there any acceptable risks, how will informed consent be sought, how will confidentiality be respected?). Therefore, these issues need to be addressed in your proposal.

Identifying a Research Question/Problem

Your research question should be both:

  • Useful (extending knowledge relevant to health care that might contribute to changes in practice)
  • Do-able (feasible given resource constraints)

This can be achieved by identifying a practice related problem, considering complaints, policy initiatives and service delivery changes, or by reading articles in journals.

Justify the Research, Research Design and Methods

What is the current state of knowledge in your topic area? Has your research question already been answered? If not, what are the typical methods used to address research questions similar to yours? What other methods might be appropriate? You will need to provide a brief critical review of relevant literature and state how your study will contribute to this field of study.

Given your research question, what types of data will be collected to answer this (e.g. quantitative and/or qualitative)? What is the most appropriate research strategy (e.g. experiment, survey, case study, action research etc) and what methods will you use (e.g. observation, questionnaire, interviews etc)?

Resources and Constraints

What factors should you take into account?

  • Time – do you have enough to prepare, conduct, analyse and write up the study?
  • Expertise – do you have knowledge and skills in the particular topic & method(s)?
  • Participants – can you secure access to the necessary participants (e.g. patients, relatives, work colleagues) within the ethical guidelines and in the relevant time frame?
  • Financial resources – will you need to consider acquiring extra staff and/or equipment, how will you cover the costs of conducting the research (photocopying, postage, travel etc), can this be approved by your manager or do you need to secure funding?

Writing a Research Proposal

A research proposal is a detailed statement identifying what you intend to do; why; how; and with whom. It indicates your ability to conduct the study and provides an opportunity:

  • For you – to clarify your thoughts
  • For others – to examine these (importance, feasibility, ethics, funding etc)

Components of an Research Proposal

  • Title of the proposed project
  • Name of the student/researcher
  • Brief summary and problem statement
    Aims & objectives
  • Rationale/justification (why the research is important and should be conducted)
  • Brief literature review (scientific background)
  • Brief description of research design (approach, strategy, methods, analysis)
  • Ethical considerations (consent of participants, other clinicians, participant information sheet)
  • Timescale/plan
  • Any resource implications (how costs will be met, any funding required/secured)
  • Proposed outputs (dissemination, feedback to participants)

Research Proposals – Questions to Ask

Is it realistic?

  • Have I the necessary skills & time to carry it out?
  • Is it ethical?
  • Have I considered how my sample will be selected, how informed consent will be achieved, how data will be collected, stored (and destroyed) and disseminated whilst maintaining confidentiality and complying with the Data Protection Act?

Is it clear?

  • Have I used simple language & not jargon?
  • Have I explained technical terms?
  • Have I included an indication of the kinds of questions I will be asking, or observations I will be recording?

Can I anticipate any problems?

  • Have I covered each section thoroughly?
  • Are there any weaknesses?

Research Proposal
Research Proposal

In this article we have identified what is generally required of researchers when they submit proposals for ethical approval. The assignment for this module involves preparing a similar proposal.

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Trend Forecasting Steps For Analysis

Trend Forecasting Steps

Fashion forecasting is generally a career that involves focusing on upcoming trends in the fashion industry. Fashion and trend forecasting is the future determination of mood, behavior and purchasing habits of consumer at a given time of season. It does not only involve determination of markets, consumers in terms of age, their locations and income but also inquire deeply to get to know what they purchase depending on their culture, beliefs, moods as well as geographical location.  Fashion and trend forecasting is more reliant on fashion cycle and plays a significant role in introductory stage of consistent fashion cycles.

Fashion and trend forecasting involves a series of activities in each of the area it is dealing with. For example it looks at the; season, target market, consumer, colors, fabrics, silhouette, texture and usage. Therefore, comprehending fashion and trend  forecast is not only crucial in determining the success of the ultimate object of the designer but also enhances the continuous repetition of sales in future seasons as well as promoting the fashion cycles.

Unlike in the past when trend forecasting was done manually, current trend forecasting is done using technological forecasting methods although they have been criticized for reducing creativity by most designers. Most trend forecasting are determined by the forecasting method applied by the ultimate user and it is therefore crucial to determine the most appropriate method of trend forecasting in any individuals business model. Generally, any trend forecasting methods involve the following steps (Hines, 2007);

The first step is Problem definition. Although this is the hardest section of forecasting, it is the most important. This step requires keen analysis of how the forecasts will be used, who needs the forecasts as well as how the forecasting technique suits within the firm needs the forecasts. A forecaster should therefore use enough time to every individual who will take part in data collection, keeping the data as well as applying the forecast for future planning. Then gathering of information follows whereby in most cases, statistical or quantitative data and qualitative data are the ones required. Therefore, the collectors of the data should be expertise who can be able to receive the qualitative information from the respondents who are usually the customers if there is no adequate quantitative information (Wong, 2010).

The third step is preliminary analysis, also called exploratory analysis. In this step, the forecaster should consider whether or not there are consistent pattern that lead to significant trend, whether or not there is evidence of business cycles, the presence of outliers in the information that need explanation as well as the extent of relationship between variables present for analysis.

The fourth step is choosing and fitting models. The best method of trend forecasting should depend on the historical data present, the application of the forecasts as well as the extent relationship between the forecasts available and explanatory variables. Some of the methods that can be arrived at includes; exponential smoothing model, ARIMA model, vector autogression, neural networks among others (Wong, 2010).

The last step involves the use and evaluation of the forecasting model. The success of the model can only be determined after the data for the forecast time has been present after which various methods are applied to assess the success of the model.

Research Methodologies

As earlier stated, the main data required in trend forecasting is qualitative, quantitative and mostly commonly, a combination of the two.

The quantitative research methodology start right from the bottom, where agencies and even the manufacturers either inquires directly from the customers on their purchasing preferences or the organization may record the consumers buying habit in a duration of a given time. The consumer’s response is recorded and used to determine preference for some specific garments, accessories or any other product on research, colors, and sizes among other factors of a product. Surveys through mail, customer response or phones are carried through publication as well as contracting market research organizations for manufacturers and as well as retailers.

The survey questions usually relate to life style, income, shopping habits as well as fashion preference. The customers who participate in these surveys are selected by the research company although they should suit with manufacturers or retailers requirements. Informal discussion with consumer enable researchers get information through asking questions to customers about what they would prefer to purchase, the types they prefer to purchase which is currently present as well as the change in products they require and are not available or they cannot reach. Most researchers use small scale retailers because of their contact and conversation with the customers.

Trend Forecasting Steps
Trend Forecasting Steps

The quantitative methodology entails the use of statistical data or information to determine the trend in customer demands and hence forecast on producing what the consumers purchase the most. Statistical data for fashion sector is easily obtainable without necessarily going to the field because it is available in manufacturers or retailers sales records (Hines, 2007).

From such records, the manufacturers can determine which garments, color of the product, size as well as the fashion preference of the consumer. After that, the manufacturer should be able to determine which fashion product should be produced more depending on sales experienced at each season of the year. It is valuable noting that a well-balanced combination of the qualitative and quantitative research methodologies is bound to boost the success of the model selected for trend forecasting.

Conclusion

This paper has attempted to show that the fashion industry has one main purpose; to offer desirable as well as appealing product to not only satisfy the customer needs, demands and aspire to have them but to also keep the product selling in the subsequent business cycles with a similar season. Every successful trend forecast must commence with the consumer through determination of the consumer’s needs to the market as well as the ability to make the consumer adjust the marketplace to his preferences and lifestyles. The paper has also expounded on the two critical methodologies used in forecast research i.e.  the qualitative and quantitative methodologies. It has also emphasized on the need to combine the two methods in order to attain the best results of the model of forecast selected.

References

Hines, T., & Bruce, M. (Eds.). (2007). Fashion marketing: contemporary issues. Routledge.

Wong, W. K., & Guo, Z. X. (2010). A hybrid intelligent model for medium-term sales forecasting in fashion retail supply chains using extreme learning machine and harmony search algorithm. International Journal of Production Economics, 128(2), 614-624.

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Mixed Method Research Design

The Mixed Method in Research Design

The mixed method approach to evaluating research data may be applicable to studies that are designed to gather both qualitative and quantitative information. This technique is often used in disciplines such as psychology, sociology or certain types of medicine. The continued development of these fields may depend on data that is derived from standardized scales or rating systems in addition to that gleaned from interviews, ‘focus group’ sessions and other similar tools. Therefore, the mixed method may be appropriate in a new project on a complex issue or situation that generates complex and highly individualized answers to research questions. Examples of these may include the societal impact of homelessness or the treatment of a lost or diminished sense. The data here may need to cover detailed and varied feedback (or ‘self-reports’) on the effect(s) of these target variables, as well as scores from formal quantitative tools typically used within the research community in question. One data type does not give a complete ‘picture’ of the outcome(s) without the other. Therefore, a methodology that incorporates both to analyse the data set as a whole is necessary.

The mixed method may combine and synthesize this data through a process called triangulation. This may involve the conversion of qualitative data into quantitative data. Such a form of triangulation is most applicable to data resulting from the administration of structured interviews or surveys, provided that data is sufficiently standard or homogeneous across respondents to be coded or scored effectively (i.e. without bias or other forms or statistical inadequacy). In this way, it may be converted to quantitative data, and compared or analysed in accordance with the requirements of the study design (e.g. subjected to a form of analysis such as a paired t-test). On the other hand, the qualitative data may be too individualized and/or complex to be coded. In this case, a thematic analytical technique may be used, incorporating findings such as significant differences among the quantitative data points as a theme or concept.

Mixed Method Research Design
Mixed Method Research Design

The aim of triangulation is the full integration of both data types to generate contiguous concepts or conclusions. This leads to another advantage of the mixed method: i.e. that it can address research aims that do not stem from standard null hypotheses. Questions, in other words, along the lines of ‘Does this novel treatment result in an improvement in the life quality of patients with hearing loss?’ rather than statements such as ‘This treatment improves hearing loss [in comparison to an existing alternative]’ to be confirmed or denied.

The mixed method is not, however, without disadvantages or detractors. Critics of this methodology often cite the risk of the ‘incompatibility paradox’; the probability that one data type will be inadequately analysed compared to the other. A prominent example of this risk is known as ‘pragmatism’, or the perception that researchers who use the mixed method value ‘experiential data’ (i.e. self-reports recorded from respondents) at the expense of quantitative data. The use of the mixed method may also be subject to preconceptions, judgement or other forms of observer bias that a researcher may impose on qualitative data in the course of its collection. These risks can be ameliorated, mainly through the skill and training of the individual researcher. Under these conditions, the mixed-method technique can be applied to generating full, comprehensive conclusions for non-standard research questions.

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References

Brown RA, Kennedy DP, Tucker JS, Golinelli D, Wenzel SL. Monogamy on the Street: A Mixed Methods Study of Homeless Men. Journal of Mixed Methods Research. 2013;7(4):328-346

Windsor LC. Using Concept Mapping in Community-Based Participatory Research A Mixed Methods Approach. Journal of mixed methods research. 2013;7(3):274-293

Robson C. Real World Research. 2 ed. Oxford: Blackwell; 2002

Mertens DM, Hesse-Biber S. Triangulation and Mixed Methods Research: Provocative Positions. Journal of Mixed Methods Research. 2012;6(2):75-79

Lieber E, Weisner TS. Meeting the practical challenges of mixed methods research. SAGE handbook of mixed methods in social and behavioral research. 2010;2:559-579

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