The Archaeologist’s Laboratory

Jochim, Michael A.; Dickens, Roy S.

doi:10.1007/b110579

Cited by 27 publications

(4 citation statements)

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“…The statements in the questionnaire are analyzed using median to describe the central tendency. In analyzing ordinal data, median is more appropriate than mean because mean is less susceptible to data outliers and mean does not give meaningful value to the level of perception (28,29).…”

Section: Methodsmentioning

confidence: 99%

Assessing E-Learning Agility in the Indonesian Public Sector

Pratiwi¹,

Krismiyati²,

Wahyuadianto³

et al. 2022

KSS

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E-Learning has been used extensively in the public sector during the coronavirus pandemic. However, the lack of IT capability has led to irresponsive user experience measures. Agile bureaucracy is often mentioned as a set of values to respond to uncertainty during the robust demand of online interactions. Previous studies including systematic literature reviews have suggested that agile bureaucracy in the public sector is hindered by a culture of hierarchy and a lack of IT competency. Using empirical data that was derived from actual experiences, this study aimed to: 1) investigate participant perceptions of agility in e-learning for civil servants in Indonesia; and 2) recommend interventions to deal with the hinderances and prerequisites for agile bureaucracy in e-learning. This research collected data through open-ended interview questions and online surveys, and data were analyzed using the Atlas.ti software. This study considered several agile bureaucracy principles in e-learning, such as continuous improvement, collaboration, merit-based management, responsive and bottom-up decision making, and flexible support. The findings suggested that bottomup decision-making and competency-based human resource management were two critical challenges in agile e-learning provision. Further, this study recommends practical measures that can be taken by e-learning providers to solve these challenges. Keywords: agile bureaucracy, training, competency development, e-learning

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Section: Methodsmentioning

confidence: 99%

Assessing E-Learning Agility in the Indonesian Public Sector

Pratiwi¹,

Krismiyati²,

Wahyuadianto³

et al. 2022

KSS

View full text Add to dashboard Cite

show abstract

“…Precision is often associated with accuracy, but there are key differences; accuracy refers to how close a measurement is to a true value (p. 487). Repeatability (or reliability) refers to the extent to which the measurement yields the same results in different trials (Banning, 2000: 11). These terms have somewhat common elements, but it is critical to recognize the differences between each term as they relate to different terms of data evaluation and can easily be misused.…”

Section: Methodsmentioning

confidence: 99%

“…When measuring metric data, the appropriate degree of accuracy and resolution needs to be considered (Banning, 2000: 10–11; Lyman and VanPool, 2009: 487). Ideally, the exact accurate value for each decorative element is the goal.…”

Section: Methodsmentioning

confidence: 99%

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Evaluating precision and repeatability of hand calipers

Dorland

2016

North American Archaeologist

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Often, statistical evaluations of metric data are overlooked in ceramic studies. This paper evaluates degrees of precision and repeatability through the application of a coefficient of variation analysis and a repeated measures ANOVA. First, the author assessed the use of calipers for measuring metric data that pertains to decorative elements. Second, the author assessed the degree of statistical difference between measurements taken and measurements that have been rounded, a technique used to account for intra-observer error. The results demonstrate that the precision and repeatability of calipers is suitable for effectively measuring metric data values, and the precision of non-rounded values does not differ greatly from rounded values. The author argues that calipers are an effective metric measuring aid that further contribute to studies of personal actions and thought processes of potters. As a result, archaeological focus can integrate a micro-scale understanding of potting communities to consider finding individual variation and the learning landscapes of inexperienced potters.

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Poisson and Binomial Distribution

Palmisano

2018

The Encyclopedia of Archaeological Sciences

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Probability distributions are important tools for assessing the probability of the outcomes that occur. In particular, archaeologists have used the binomial and the Poisson distributions in order to model the likelihood of discrete archaeological phenomena. This section introduces these two methods and shows practical examples where they can be applied to archaeological contexts. The two distributions are, therefore, comparatively described and evaluated on their similarities and differences. The binomial distribution models the probability of “successes” and “failures” in a fixed number of trials. Instead, the Poisson distribution counts the occurrences occurring in a given unit of time or space with no fixed cutoff.

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The Archaeologist’s Laboratory

Cited by 27 publications

References 0 publications

Assessing E-Learning Agility in the Indonesian Public Sector

Assessing E-Learning Agility in the Indonesian Public Sector

Evaluating precision and repeatability of hand calipers

Poisson and Binomial Distribution

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