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Observation is a neglected data collection method in higher education research. Yet observation holds out the promise of seeing what people actually do, rather than what they say they do (in interviews or surveys) or write down that they do (in documents). It may also be pursued quantitatively and/or qualitatively, using a highly structured data collection instrument or in an open-ended and flexible fashion, carried out live or using recorded material. This chapter explores the limited existing literature on the use of observation in higher education research, speculates on the reasons for its lack of use, and argues for its greater usage in the future.

Several studies have observed that stocks tend to drop by an amount that is less than the dividend on the ex-dividend day, the so-called ex-dividend day anomaly. However, there still remains a lack of consensus for a single explanation of this anomaly. Different from other studies, this dissertation attempts to answer the primary research question: how can investors make trading profits from the ex-dividend day anomaly and how much can they earn? With this goal, I examine the economic motivations of equity investors through four main hypotheses identified in the anomaly's literature: the tax differential hypothesis, the short-term trading hypothesis, the tick size hypothesis, and the leverage hypothesis.

While the U.S. ex-dividend anomaly is well studied, I examine a long data window (1975–2010) of Thailand data. The unique structure of the Thai stock market allows me to assess all four main hypotheses proposed in the literature simultaneously. Although I extract the sample data from two data sources, I demonstrate that the combined data are consistently sampled. I further construct three trading strategies – “daily return,” “lag one daily return,” and “weekly return” – to alleviate the potential effect of irregular data observation.

I find that the ex-dividend day anomaly exists in Thailand, is governed by the tax differential, and is driven by short-term trading activities. That is, investors trade heavily around the ex-dividend day to reap the benefits of the tax differential. I find mixed results for the predictions of the tick size hypothesis and results that are inconsistent with the predictions of the leverage hypothesis.

I conclude that, on the Stock Exchange of Thailand, juristic and foreign investors can profitably buy stocks cum-dividend and sell them ex-dividend while local investors should engage in short sale transactions. On average, investors who employ the daily return strategy have earned significant abnormal return up to 0.15% (45.66% annualized rate) and up to 0.17% (50.99% annualized rate) for the lag one daily return strategy. Investors can also make a trading profit by conducting the weekly return strategy and earn up to 0.59% (35.67% annualized rate), on average.

Classroom management is a prerequisite for effective instruction, yet research indicates that not all teachers implement evidence-based classroom management skills (CMS) in their classroom. Therefore, efficient professional development models are necessary to increase teachers’ use of CMS, but those models are predicated on valid and reliable screening tools to identify teachers CMS performance. This study is a psychometric evaluation of a direct observation CMS screening tool for elementary school teachers that can be used as part of a targeted CMS professional development model. Based on a three-facet generalizability study, the primary source of variance across observations was differences among teachers and differences across observations. A decision study was conducted and indicates that a generalizable estimate from the CMS screening tool requires four 30-min observations. These results are compared with prior research and recommendations for future research are discussed.

This chapter focuses on the ethnographic research approach that I employed in a service marketing study. The first part briefly describes ethnography’s key characteristics, that is, emergent research logic, prolonged fieldwork, and multiple modes of data collection, where the main method is observation. The second part discusses the data collection methods: participant observation, informal discussion, interview, and document analysis. This section describes in detail how these techniques were used in practice and highlights the key challenges I faced, especially related to the observations, and how I managed these challenges. The third part describes the case, field setting, informants, and field relationships. The development project that I studied concerned a bank’s website and project members from the bank and different consultant agencies represent the study’s informants. The fieldwork lasted for about one year and covered the entire development process from the initial stages to the launch, and some time after. The chapter ends with a thorough discussion about the research criteria of validity, reliability, and generality, and the coping tactics that I used in this study to enhance these. Prolonged fieldwork, multiple modes of data collection, reflexivity, and specification of the research are among those important tactics that this last section discusses in detail.

For this discussion, assume there are n sample observations of the dependent variable y at unique locations. In spatial samples, often each observation is uniquely associated with a particular location or region, so that observations and regions are equivalent. Spatial dependence arises when an observation at one location, say y i is dependent on “neighboring” observations y j, y j∈ϒi. We use ϒi to denote the set of observations that are “neighboring” to observation i, where some metric is used to define the set of observations that are spatially connected to observation i. For general definitions of the sets ϒi,i=1,…,n, typically at least one observation exhibits simultaneous dependence, so that an observation y j, also depends on y i. That is, the set ϒj contains the observation y i, creating simultaneous dependence among observations. This situation constitutes a difference between time series analysis and spatial analysis. In time series, temporal dependence relations could be such that a “one-period-behind relation” exists, ruling out simultaneous dependence among observations. The time series one-observation-behind relation could arise if spatial observations were located along a line and the dependence of each observation were strictly on the observation located to the left. However, this is not in general true of spatial samples, requiring construction of estimation and inference methods that accommodate the more plausible case of simultaneous dependence among observations.

This chapter focusses on the complexity of observation, considering its role in lesson study, following a broader discussion of how observation is generally understood in teaching contexts. The authors argue that lesson study observation is formative and should not be performative in focus. In lesson study cycles, observation is a process conducted among peers ideally in a spirit of mutual support and collaborative inquiry, seeking to find answers to pedagogic challenges rather than measuring the effectiveness of individual teachers.

This paper aims to explore the impact of the data observation period on the computation of altmetric measures like velocity index (VI) and half-life. Furthermore, it also attempts to determine whether article-level computations are better than computations on the whole of the data for computing such measures.

The complete publication records for the year 2016 indexed in Web of Science and their altmetric data (original tweets) obtained from PlumX are obtained and analysed. The creation date of articles is taken from Crossref. Two time-dependent variables, namely, half-life and VI are computed. The altmetric measures are computed for all articles at different observation points, and by using whole group as well as article-level averaging.

The results show that use of longer observation period significantly changes the values of different altmetric measures computed. Furthermore, use of article-level delineation is advocated for computing different measures for a more accurate representation of the true values for the article distribution.

The analytical results show that using different observation periods change the measured values of the time-related altmetric measures. It is suggested that longer observation period should be used for appropriate measurement of altmetric measures. Furthermore, the use of article-level delineation for computing the measures is advocated as a more accurate method to capture the true values of such measures.

The research work suggests that altmetric mentions accrue for a longer period than the commonly believed short life span and therefore the altmetric measurements should not be limited to observation of early accrued data only.

The present study indicates that use of altmetric measures for research evaluation or other purposes should be based on data for a longer observation period and article-level delineation may be preferred. It contradicts the common belief that tweet accumulation about scholarly articles decay quickly.

Several studies have shown that altmetric data correlate well with citations and hence early altmetric counts can be used to predict future citations. Inspired by these findings, majority of such monitoring and measuring exercises have focused mainly on capturing immediate altmetric event data for articles just after the publication of the paper. This paper demonstrates the impact of the observation period and article-level aggregation on such computations and suggests to use a longer observation period and article-level delineation. To the best of the authors’ knowledge, this is the first such study of its kind and presents novel findings.