3.5 Research Procedure
3.5.1 Ethnoscience Database Development
3.5.2.1. Ethnoscience Database (ED) Computer Programme Design
Research and product/package development design in education according to Nworgu (1991) is a process whereby educational products such as textbooks, equipment or curricular are developed and trial tested in the field to ensure their effectiveness. Designing and developing Ethnoscience Database computer programme involve steps similar to any problem-solving task.
There were five main steps in the programming process. These are:
i) Defining the problem ii) Entering the Data iii) Formatting the Database
iv) Using the Database Tools in Ethnoscience Database
v) Ethnoscience Database Verification, Testing and Validation Defining the Problem
The task of defining the problem involves identifying what one knows (input-given data), and what one wants to obtain (output-the result). What is known is the Ethnoscience Database and what is to be obtained is a data storage and retrieval system.
In order to make the Database information easily available, a storage and retrieval system was developed using the latest version of Microsoft Excel (2010 version) to create a database file. It was then saved as Excel 97-2003 workbook for easier access by the expected users. An average computer user feels more comfortable with the Excel application than Access or any other more complicated database and can easily control the programme himself.
The steps involved in developing the Database using Microsoft Excel are:
71 Entering the Data
The basic format for storing data in an Excel database is a table. This involves entering the data in rows and columns. The rows in database format are referred to as RECORDS while the columns are referred to as FIELDS.
Each field has a heading to identify the data it contains. In this case, there are eight (8) fields. These are:
a. Code
b. Science related common Yorùbá sayings
c. Cultural belief from which the saying was derived.
d. Cultural explanation of the sayings e. Related modern scientific concepts f. Explanation of modern science concepts g. Classification of the sayings
h. Intervention
i. Related science concepts
The records are one hundred and five in number. The first record contains the title of the database i.e. ETHNOSCIENCE DATABASE. The second record contains the headings of each field. The remaining one hundred and three records contain full information about each of the collected science related common sayings. Once the table has been created, Excel's data tools can be used to search, sort, and filter records in the database to find specific information. Effort was made to make sure that the data were correctly entered to prevent data errors that are caused by incorrect data entry. The problem of incorrect data entry has been indicated in many problems related to data management. In entering the records, the following guidelines were taken into consideration as suggested by French (2012):
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1. Leave no blank rows in the table being created, not even between the headings and the first row of data.
2. A record can contain data about only one specific item.
3. A record must also contain ALL the data in the database about that item. There can't be information about an item in more than one row.
Formatting the Database
The database was then formatted using the following guideline suggested by French (2012) by:
1. Drag selecting cells A1 to H1 in the spread sheet.
2. Clicking on the Merge and Centre icon on the Formatting Toolbar to centre the title.
3. Clicking on Fill Colour icon to open the background colour drop down list while still selecting cells A1 to H1.
4. Choosing Dark Blue (Text 2, 80%) from the list to change the background colour of cells A1 - H1 to dark Blue.
5. Clicking on the Font Colour icon again (a large letter “A ") to open the font colour drop down list.
6. Choosing white (Background 1) from the list to change the colour of the text in cells A1 - H1 to white.
7. Drag selecting cells A2 - H2 on the spreadsheet.
8. Clicking on the Fill Colour icon on the Formatting Toolbar to open the background colour drop down list.
9. Choose Blue (Accent 1, Lighter 80%) from the list to change the background colour of cells A2 - E2 to light blue.
10. Drag selecting cells A3 - H105 on the spread sheet.
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Alternatively, having saved the data on Microsoft Excel spread sheet, select for top cells from the columns of data you have created, then click on Data in the Menu Bar, select and click Filter which automatically turns the spread sheet into a database. To save database, go to File on the Menu Bar, select Save as, and then change the format to XML Spreadsheet.
Using the Database Tools in Ethnoscience Database
Database tools are located under the drop down arrows beside each field name and can be used to filter the data. Retrieving information from the database can be done by filtering data in the Database following these steps:
1. Click on the drop down arrow next to CODE field name or any of the field names.
2. Type the key word you want information about into the search box.
3. Click OK.
The record containing the information is then displayed. Use undo to go back to the full database.
Ethnoscience Database Verification, Testing and Validation
Software verification provides objective evidence that the design outputs of a particular phase of the software development life cycle meet all of the specified requirements for that phase of the software development (U.S. Department of Food and Drug Administration, 2002).
Software testing is one of many verification activities to confirm that software development output meets input requirements. Meanwhile, software validation according to U.S. Department of Food and Drug Administration refers to confirmation by examination and provision of objective evidence that software specifications conform to user's need and intended uses that the particular requirements implemented through software can be consistently fulfilled. In short, verifications, testing, inspections, examinations, and other verification techniques are embedded in validation.
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A documented software requirements specification provides a baseline for both validation and verification (U.S. Department of Food and Drug Administration, 2002). Verification, testing and other tasks that support software validation occur during each phase of the software life cycle activities. Software requirements specification was evaluated to verify for accuracy, completeness, consistency, testability and clarity among others. The evaluators who are software Engineers / Programmers attested to its compliance. Software testing entails running software products under known conditions with defined inputs and documented outcomes that can be compared to the predefined expectation (U.S. Department of Food and Drug Administration, 2002). Alpha testing, which is an actual operational testing by the potential users or customers or an independent team at the developer‟s site was conducted. Complex validation was however unnecessary since the database is a simple one.