Validating Utility of TEIM: A Comparative Analysis

Concrete efforts to integrate Software Engineering and Human Computer Interaction exist in the form of models by many researchers. An unconventional model called TEIM (The Evolved Integrated Model) of Software Engineering and Human Computer Interaction was proposed by us. There is a need to establish correlation with prior models as well validate utility of TEIM. In this paper product PS designed using SE-HCI integration model TEIM is evaluated by making a comparative analysis. For evaluation UGAM and IOI tools designed by DR.Anirudha Joshi are used. Our analysis showed that correlation of TEIM exists with prior models. Regression analysis showed that high correlation exists between TEIM and prior model.


INTRODUCTION
Better user experience is an oft expressed quality of the products designed nowadays.Many efforts in this regard lead to various proposals of smooth integration of SE(software engineering ) processes with HCI(human computer integration) for product development were done [1], [3], [4], [5], [8], [10], [11], [12].We got inspired by these and designed a product application by name PS(Personal Secretary) using SE-HCI integration model of [1] and adding empathy map [7], [9] to it.The steps used for designing PS evolved into a new SE-HCI integration model by name TEIM [2].

II. VALIDATING UTILITY OF TEIM
Dr.Anirudha Joshi in [1] had proposed UGAM (Usability Goals Achievement Metric) to measure user experience goals and IOI (Index of Integration) to measure extent of integration of HCI activities in SE processes.
We used UGAM and IOI to evaluate PS in this paper.Section III explains UGAM score calculation for PS, section IV explains IOI score calculation for PS and section V explains mathematical and comparative analysis of PS vis-à-vis TEIM.
For mathematical and comparative analysis statistical methods of regression, Pearson's coefficient, ANOVA are used.

III. USABILITY GOALS ACHIEVEMENT METRIC
Usability Goals Achievement Metric (UGAM) proposed by [1] is a product metric that measures the quality of user experience.[1]  Goals: High level user experience goals.

A. UGAM components
 Goal parameters: Goals divided in to goal parameters.
 Weight: Weights are in the range 0-5 indicating least relevant to most relevant.
 Score: Scores are in the range 0 to 100 broken down to four categories 0-worst user experience, 25-bad, 50undecided state, 75-good and 100-best.
UGAM calculation for TEIM Model is in Table 1.UGAM parameter labels are in Figure 1.The average weight assigned is 2.8 which is in the range 2.4 to 3.4.As per UGT (Usability Goal Setting Tool) the weight assigned is balanced.UGAM tool proposed by Joshi. A. et al., [1] is used to measure user experience of PS designed by us.
PS was evaluated on teaching staff of Computer Engineering dept. of BSCOER, Pune by us and scores were assigned.UGAM was calculated [1] using the formula ∑ (W p X S p )/ ∑W p where Wp is the weight of the goal parameter p and S p is the score of the goal parameter p.

IV. UGAM AND IOI RELATIONSHIP
In [1] data from industry projects was available in the form of 61 industry projects UGAM and IOI scores .We could not get access to such data so our reference data were the UGAM and IOI scores of Joshi. A. et al. [1].
Using this reference data and extended waterfall model [8] we used the same techniques [1] of evaluation for establishing relationship between UGAM and IOI as well relationship between our UGAM + IOI scores vs. [1] scores .Methods used to establish correlation between and their results are as followed:  Pearson's Correlation: Refer Table III   .9 to 1 very high correlation  .7 to .9 high correlation  .5 to .7 moderate correlation  .3 to .5 low correlation Very high positive correlation exists between the Variation of UGAM and the variation of IOI.There is a significant positive correlation (r= 0.99, p < 0.0005 two-tailed) between UGAM and IOI r xy = 1, adjusted r xy = 0.99.
All the above techniques including the plot drawn for UGAM vs. IOI (refer Figure 3, 4 and F) validate linear correlation between UGAM and IOI.Also Table VIII, F and E establish a linear correlation between TEIM and [1].

D. Anova Results
According to F Sig/Probability table with df(2,1) F must be at least 19.000 to reach p< 0.05.So F score is statistically significant.Hence our hypothesis is supported.

E. RK VS AJ Correlation
The range of correlation coefficient is -1 to 1. Since our result is 0.99 or 99%, it means the variables have a high positive correlation.

F. UGAM Vs IOI Calculation
The closer the points come to straight line stronger the relationship.We will express the strength of the relationship between 0 and 1.

V. CONCLUSION
We designed product PS (refer Figure 6) getting inspired from prior work of integration of Human Computer Interaction and Software Engineering processes also adding our own beliefs such as empathy map [7], [9].Whatever design steps we applied we compiled them together as a new integration model of SE and HCI and called it as TEIM-The Evolved Integration Model of SE and HCI [2].Dr. Anirudha Joshi's work in this area is here [8].Dr. Anirudha Joshi's tools UGAM and IOI were used to calculate UGAM score (43.15) and IOI score (46.74) respectively for the product PS.Though scores were on lower side as compared to [1] (beta version of PS was tested) they showed linearity and strong correlation.

Figure 3 .Figure 4
Figure 3. UGAM VS IOI CORRELATION for Pearson Coefficient calculation and A for the results. Linear Regression: Refer Table IV, V for Linear Regression calculation and B, C for results.Interpretation Interpretation of Pearson's Correlation results: a positive Coefficient indicates values of variable A vary in the same direction as variable B. Characterizations of Pearson r:  ANOVA: Refer Table VI, VII and D for ANOVA calculations and results respectively.www.ijacsa.thesai.org A. Pearson's