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Table 1. Level of efficiency of using manual vis-a-vis alternative OMR procedure in checking test papers and analyzing Its results 1s shown 1n lable 1. As shown in Table 1, the alternative OMR procedure is more efficient in checking test papers an analyzing its results with a mean score of 1.05 (SD = 0.21) compared to the manual procedure, which obtaine a mean evaluation of 4.76 (SD = 0.72). It indicates that alternative OMR has a better ability to check an analyze test items with less amount of time, resources, and effort or performance consumed. Moreover, thi table shows how extreme the difference is between alternative OMR and manual processes with respect t time and effort consumed, "very efficient" and "inefficient" respectively. According to Karunanayak (2015), the most evident benefit of employing OMR technology in the collection of data from documents is it efficiency when compared to the manual process, which is a time-consuming and tedious task [12].

Table 1 Level of efficiency of using manual vis-a-vis alternative OMR procedure in checking test papers and analyzing Its results 1s shown 1n lable 1. As shown in Table 1, the alternative OMR procedure is more efficient in checking test papers an analyzing its results with a mean score of 1.05 (SD = 0.21) compared to the manual procedure, which obtaine a mean evaluation of 4.76 (SD = 0.72). It indicates that alternative OMR has a better ability to check an analyze test items with less amount of time, resources, and effort or performance consumed. Moreover, thi table shows how extreme the difference is between alternative OMR and manual processes with respect t time and effort consumed, "very efficient" and "inefficient" respectively. According to Karunanayak (2015), the most evident benefit of employing OMR technology in the collection of data from documents is it efficiency when compared to the manual process, which is a time-consuming and tedious task [12].

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Level of Accuracy of Data Output As presented in Table 2, both the alternative OMR and manual procedures produce very accurate results in checking test papers with a closer mean score of 1.01-1.03 (SD = 0.03 - 0.13); also, both the alternative OMR and manual procedures produce very accurate results in analyzing test papers with a closer mean score of 1.00-1.03 (SD = 0.02 - 0.12). It suggests that alternative OMR and manual procedures both provide a very precise and error-free test checking and analysis. However, the standard deviation of 0.03 - 0.02 in the alternative OMR process of checking and item analyzing, respectively, and the standard deviation of 0.13 - 0.12 in the manual process of checking and item analyzing both give a consistent difference in how "very accurate" those processes are.
Level of Accuracy of Data Output As presented in Table 2, both the alternative OMR and manual procedures produce very accurate results in checking test papers with a closer mean score of 1.01-1.03 (SD = 0.03 - 0.13); also, both the alternative OMR and manual procedures produce very accurate results in analyzing test papers with a closer mean score of 1.00-1.03 (SD = 0.02 - 0.12). It suggests that alternative OMR and manual procedures both provide a very precise and error-free test checking and analysis. However, the standard deviation of 0.03 - 0.02 in the alternative OMR process of checking and item analyzing, respectively, and the standard deviation of 0.13 - 0.12 in the manual process of checking and item analyzing both give a consistent difference in how "very accurate" those processes are.
Level of Reliability of Data Output
Level of Reliability of Data Output
Table 4. Level of efficiency of using manual vis-a-vis alternative OMR procedure in checking test As presented in Table 4, there is a significant difference between the mean evaluation of alternative OMR and Manual procedures in terms of their level of efficiency in checking test papers and analyzing their results. The figures in the table suggest that alternative OMR and manual procedures differ by 3.71 points in favor of the alternative OMR. This mean difference is statistically significant when tested at .01 level, which produces a Cohen’s d value of 7.00 that signifies a large effect size. It can be inferred from Table 4 that alternative OMR is a more efficient procedure for checking and analyzing tests compared to the manual process. According to Virtus (2019), efficiency is the most evident benefit of employing optical mark recognition technology to acquire data from papers. In alternative OMR, documents are scanned and typed at a rate that is several times faster than a human can [7].
Table 4. Level of efficiency of using manual vis-a-vis alternative OMR procedure in checking test As presented in Table 4, there is a significant difference between the mean evaluation of alternative OMR and Manual procedures in terms of their level of efficiency in checking test papers and analyzing their results. The figures in the table suggest that alternative OMR and manual procedures differ by 3.71 points in favor of the alternative OMR. This mean difference is statistically significant when tested at .01 level, which produces a Cohen’s d value of 7.00 that signifies a large effect size. It can be inferred from Table 4 that alternative OMR is a more efficient procedure for checking and analyzing tests compared to the manual process. According to Virtus (2019), efficiency is the most evident benefit of employing optical mark recognition technology to acquire data from papers. In alternative OMR, documents are scanned and typed at a rate that is several times faster than a human can [7].
Based on the results in Table 5, there is no significant difference between the level of accuracy of using manual vis-a-vis alternative OMR procedure in checking test papers and analyzing its results [t(48) = .913; t(48) = 1.109; p > .05)]. This result means that the two procedures showed a comparable level of accuracy when they were evaluated by the 25 teachers who served as the respondents of the study. In fact, they are both evaluated as “very accurate”. The data shows that using an alternative OMR provides a quick assessment of a student's test results. ‘eachers, in fact, find it useful, especially in terms of its ability to compute for item analysis, which was reviously a time-consuming operation. Data on the results will almost always be readily and promptly vailable. In the absence of an alternative OMR, each document must be painstakingly checked manually efore being properly entered into a form or computer system. Although skilled individuals could become roficient with evaluating and inputting data from forms, there seems to be a real limit towards how quickly n individual could do the task [7]. Tahle 5 reveals the test of significant difference on the level of accuracv hetween manual and
Based on the results in Table 5, there is no significant difference between the level of accuracy of using manual vis-a-vis alternative OMR procedure in checking test papers and analyzing its results [t(48) = .913; t(48) = 1.109; p > .05)]. This result means that the two procedures showed a comparable level of accuracy when they were evaluated by the 25 teachers who served as the respondents of the study. In fact, they are both evaluated as “very accurate”. The data shows that using an alternative OMR provides a quick assessment of a student's test results. ‘eachers, in fact, find it useful, especially in terms of its ability to compute for item analysis, which was reviously a time-consuming operation. Data on the results will almost always be readily and promptly vailable. In the absence of an alternative OMR, each document must be painstakingly checked manually efore being properly entered into a form or computer system. Although skilled individuals could become roficient with evaluating and inputting data from forms, there seems to be a real limit towards how quickly n individual could do the task [7]. Tahle 5 reveals the test of significant difference on the level of accuracv hetween manual and
Table 6. Level of reliability of using manual vis-a-vis alternative OMR procedure in checking test papers and analyzing its results Table 6. Level of reliability of using manual vis-a-vis alternative OMR procedure in checking test As described in Table 6, there is no significant difference between the level of reliability of using manual vis-a-vis alternative OMR procedure in checking test papers and analyzing its results [t(48) = .825; t(48) = 1.107; p > .05)]. This result means that the two procedures showed a similar level of reliability when they were evaluated by the 25 teachers who served as the respondents of the study. In fact, they are both evaluated as “very reliable”. Ronnel P. Cuerdo, Michael Jomar B. Ison, Christian Diols T. Ofiate International Journal of Theory and Application in Elementary and Secondary School Education (IJTAESE), Vol. 3 (2), 61-75 Effectiveness of Automation in Evaluating Test Results Using EvalBee as an Alternative Optical Mark Recognition (OMR): A Quantitative-Evaluative Approach from a Philippine Public School
Table 6. Level of reliability of using manual vis-a-vis alternative OMR procedure in checking test papers and analyzing its results Table 6. Level of reliability of using manual vis-a-vis alternative OMR procedure in checking test As described in Table 6, there is no significant difference between the level of reliability of using manual vis-a-vis alternative OMR procedure in checking test papers and analyzing its results [t(48) = .825; t(48) = 1.107; p > .05)]. This result means that the two procedures showed a similar level of reliability when they were evaluated by the 25 teachers who served as the respondents of the study. In fact, they are both evaluated as “very reliable”. Ronnel P. Cuerdo, Michael Jomar B. Ison, Christian Diols T. Ofiate International Journal of Theory and Application in Elementary and Secondary School Education (IJTAESE), Vol. 3 (2), 61-75 Effectiveness of Automation in Evaluating Test Results Using EvalBee as an Alternative Optical Mark Recognition (OMR): A Quantitative-Evaluative Approach from a Philippine Public School
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EducationMeasurement and evaluation in educationOptical Mark RecognitionAutomated Evaluation
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