Data Collection Tools. Contractor’s data collection systems shall be able to operate both in areas with cellular service available and in areas without cellular service. All data systems shall be compatible with existing Geographic Information System (GIS) systems, currently provided by Esri or similar products. If the User Agency deems it necessary, the Contactor data system shall be able to rapidly integrate with the User Agency data systems via API integration.
Data Collection Tools. During HIVST implementation, it is important to integrate HIVST monitoring into existing tools and monitoring programs. For instance, some testers may have been previously diagnosed with HIV and some may already be on ART. Revising national HIV testing and ART registers to include an additional column for HIVST is a simple way to streamline HIVST monitoring and the reporting of uptake. Questions on HIVST can also be included in special surveys, such as in a demographic and health survey (DHS) or in integrated bio- behavioral surveillance (IBBS). Additional HIVST-specific monitoring and reporting tools may be needed, such as providing distributors with tablet- or paper-based tools to collect data on people receiving HIVST kits across various service delivery points. For instance, when distributing self-test kits a client data card or HIVST register can be used to determine who is accessing HIVST. Surveys conducted by telephone or through apps or short messages are feasible options in some settings to estimate HIV positivity and linkage following HIVST, as indicated in the M&E indicator table for the different distribution models. See examples of HIVST Data collection tools in the Annexes.
Data Collection Tools. Multiple study tools were employed during the execution of this baseline study. Children aged 3-
Data Collection Tools. Firstly, I conducted a one-to-one semi-structured interview (Appendix D), which is considered a flexible form of interview (Xxxxx & Xxxxx, 2005), with the purposefully selected teachers. Interviewing not only analyses words and reports respondents’ detailed answers, it also allows the interviewed to “speak in their own voice and express their own thoughts and feelings” (Xxxx, 2007, p. 96). Each interview gave me substantial answers on various aspects of collaboration: perceptions, initiation and strategies, motivating factors, challenges and components of successful collaboration. Secondly, I was a non-participating observer (Yin, 1994) of collaborative and staff meetings. The focus of my observation was based on what teachers answered about collaboration in the interviews. The chosen teachers were requested to allow me access to one of their collaborative meetings on a school improvement or another collaborative project. The purpose of the observation was to see how they communicated, made shared decisions, built consensus, ensured equal participation, resolved issues and distributed roles and responsibilities. While watching and listening to their discussions, I was making notes in the specially designed observation form (Appendix E). Altogether, I conducted three observations of five teachers. The observations enabled me to compare what the participants said during the interviews with what I observed, determine what specific types of projects they collaborated and observe their collaborative tactics and communication in real time. Lastly, I attempted to obtain the schools’ documented records of school improvement projects conducted by teachers or teaching policy documents. I thought this data collection instrument could prove useful because it would allow me to compare the information received from the teachers with the recorded information in the documents. Besides, document analysis is mainly used as a complementary instrument (Xxxxx, 2009) to other data collection tools in the qualitative research method, primarily serving as a triangulation means in the study of the phenomenon (Xxxxxx, 1970). Unfortunately, I received no access to the official documents. However, two teachers shared their meeting minutes of collaborative projects with me which helped to a certain extent with the analysis of the findings. All three data collection instruments are different methods of collecting information, but they all equally helped me with cross-checking the valid...
Data Collection Tools. I have chosen a semi-structured, open-ended interview as an appropriate data collection tool for current study. According to Xxxxx et al. (2018), interviews include more than simple data collection. It is a progression towards the exchange of perspectives between two persons on a mutually engaging issue. They share their individual worldview and evaluate the scenario from their own perspective (Xxxxx et al., 2018). Xxxxx et al. (2018) claim that an interview is adaptable since information can be gathered through both verbal and nonverbal channels. The framework of an interview allows for spontaneity, and the interviewer is permitted to explore deeper into responses. By requesting additional information, the researcher can acquire a clearer image and a deeper knowledge of the participants' responses, which can be valuable to the research. More specifically, the researcher conducted semi-structured one-on-one interviews. The researcher developed an interview protocol that comprises interview information and instructions, interview questions, and a place for extra notes and comments (Xxxxxxxx, 2014). The protocol for the interview included interview material and directions, interview questions, and space for extra notes and reflections. The interview protocol comprised 18 questions and included four blocks covering four research sub-questions (see Appendix B). It also included several opening questions that aid in elucidating parents' perspectives on sexuality education in general.
Data Collection Tools. The constructs of personality traits and school burnout elements were codified into numbers using four instruments: School Burnout Inventory (SBI), Big Five Inventory (BFI), Academic Motivation Scale (AMS), and Academic Burnout Factors Questionnaire (ABFQ). School burnout was measured using the SBI developed by Xxxxxxx-Xxx and Xxxxxxxx (2005). This instrument consists of 9 statements related to school life (as cited in Xxxxxxx-Xxx et al., 2009). SBI includes such statements as: “I feel overwhelmed by my homework” and “I feel that I am losing interest in my schoolwork”. The respondents indicated the level of agreeing or disagreeing with the statement on the scale from 1 (completely disagree) to 6 (completely agree). The scores for each scale separately can be calculated summing up certain items that measure this scale. The overall burnout score can be obtained through calculating total of all items. Personality factors were measured using the BFI developed by Xxxxxxxx (1993). The BFI includes 44 statements related to personality traits (for example: “I see myself as someone who can be xxxxx”) to which respondents gave a score on the scale from 1 (disagree strongly) to 5 (agree strongly). The statements were then grouped to form a composite score for each of 5 personality factors: agreeableness, conscientiousness, neuroticism, extraversion, openness. Extraversion, agreeableness and neuroticism were measured with 8 items each, whereas conscientiousness and openness have 9 and 10 items, respectively. Each scale had a certain number of reversed items, which need to be preliminary recoded. The score for each factor was calculated summing up all the scores obtained for each item. No cumulative score can be calculated for this inventory. Academic motivation was measured using AMS developed by Xxxxxxxxx, Pelletier, Blais, Briere, Senecal, and Xxxxxxxxx (1992). The instrument consists of 28 statements, such as “I can’t understand what I’m doing at school” and “I go to school, because I want to have “the good life” later on”. Participants are given the scale (1 to 7) to show to which extent they agree or disagree with the statements. The instrument measures several instruments of academic motivation: intrinsic (knowledge oriented, experience oriented, accomplishment oriented), external (identified, introjected, external regulation) and amotivation. The score for each element is obtained through summing up the scores of items that belong to the element. Factors contri...
Data Collection Tools. Previously, Oosterbeek et al. (2010) used a difference-in-differences framework, and the outcomes of pre-and post-treatment revealed that the impact of the course had insignificant or even negative effect on students’ entrepreneurship abilities and motivation. Their findings were based solely on the outcome of a self-assessment survey (Escan test), with no qualitative data taken into account. On the contrary, the current research used online one-on-one interviews as a data collection tool to evaluate the course’s effect on students’ entrepreneurial abilities and to investigate students’ learning gains. An online interview was the most appropriate form of an interview in times of global pandemic. Significantly, the synchronous online interview helped to collect data as in face-to-face interview without missing visual cues. Therefore, the synchronous interviews were conducted via online communication platform (Google Meet) selected by students’ preference. Initially, pilot respondents tested the interview questions and evaluated their relevance for the research purpose. When the relevance and validity of the questions were confirmed, the actual interview was conducted with the research participants. Each meeting applied ten semi-structured interview questions and comprised approximately a 30-40 minutes’ conversation. The online meeting video was recorded with the student’s permission and then transcribed during the data analysis phase.
Data Collection Tools. In line with the suggestions concerning the need for studying students’ regulation of learning processes as a series of unfolding events in real time within naturalistic contexts as well as through utilising multiple sources of qualitative evidence (e.g., Xxxxxxx et al., 2010; Xxxxxx, 2011; Xxxxxxxxx et al., 2006; Xxxxx & Xxxxx, 2011; Xxxxx & Xxxxx, 2000; Xxxxxxxxx, 2008), the data of this study included classroom video observations and stimulated-recall interviews with two student groups of three, which allowed for concurrent measurement of their regulation of learning processes during scientific inquiry activities. Considering the dynamic and complex nature of regulation processes, additional data were also collected by means of semi-structured interviews with the students, informal interviews with the teacher, field notes, as well as samples of student worksheets and lesson plans. That is, these had the aim of providing further insights into understanding the nature of students’ regulation of their learning processes. The triangulation of multiple sources of data is also seen as key for achieving a comprehensive understanding and producing a valid analysis of students’ self and social regulation of learning processes within the social context (Xxxxxxx et al. 2010;
Data Collection Tools
