 |
Asia-Pacific Forum on Science Learning and Teaching, Volume 18, Issue 2, Article 3 (Dec., 2017) |
Evans (2013) analyzed 460 articles on assessment feedback in higher education over a 12-year period, and discussed the importance of authentic and performance assessment. For integrated scientific process skills, multiple scholars including Martin et al. (2005), Ngoh (2009), and Padilla (1990), referred to 5 required skills including formulating hypotheses, defining operationally, identifying, and controlling variables, experimenting, and interpreting, and making inferences.
The population of the study included 2,526 teachers and students from Thailand’s Education Region 3 in academic year 2015. Multistage random sampling was used to select the 345 vocational students and science teachers from 6 schools in Phitsanulok’s Educational Region 3, from which the total number of respondents was validated by use of Yamane’s (1973) formula, while allowing for a 4.5% error.
n = N / [1 + N ( e )2] - Where n is the sample size, N is the population size, and e is the level of precision.
A questionnaire was used to collect data from 345 teachers and students by use of multi-stage random sampling. The questionnaire items were designed using a 5-level Likert type agreement scale (Likert, 1967). The questionnaire consisted of 5 areas of questions which totaled 33 items. The reliability of the questionnaire was determined to ensure that the responses collected through the instrument were reliable and consistent. The reliability value of 0.88 was calculated by using Cronbach’s alpha (Cronbach, 1990) to ensure whether there was internal consistency within the items. The questionnaire was then used to evaluate both authentic and expected performance of scientific process skills of vocational certificate students which the scales being defined as follows: 1 = Very low, 2 = Low, 3 = Medium, 4 = High and 5 = Very high.
Data analysis was conducted in four steps. These included:
Step 1: The examination of the integrated scientific process skills of 297 vocational certificate students and 48 vocational certificate science teachers. The data was analyzed using descriptive statistics including mean ( ) and standard deviation (S.D.).
Step 2: The examination of the needs assessment of integrated scientific process skills was analyzed by use of Matrix analysis (Thammasaeng, Pupat, & Phetchaboon, 2016; Wongwanich, 2015) as follows:
Quartile 1 means above average
Quartile 2 means on average
Quartile 3 means below average with urgent improvement needed
Quartile 4 means below average.
Step 3: Prioritization and analysis of the needs assessment data was conducted by use of the modified priority needs index (PNIModified) (Silsawang, Boosabong, & Ajpru, 2014; Wongwanich & Wiratchai, 2005). To get standard scores, the needs were assessed by finding the differential value between desired outcome (I) and actual results (D) (Wongwanich, 2005). The formula for the calculation is as follows:
PNI Modified (PNIModified) = (I - D)/ D
PNI = priority needs index
I = mean desired outcome
D = mean actual results
Step 4: Last, to compare needs assessment of integrated science process skills (classified by types of institutions), analysis was conducted by use of One-way ANOVA (Thammasaeng et al., 2016).
