## 3 Materials and Methods
### Conducting Phase
#### 3.2.5 Data Extraction and Synthesis  
The basic unit of analysis was each individual article. From each study, we extracted data relevant to our study that were coded to capture the essential information that appears in categories (clusters) related to the formulated research questions. The coding categories are presented in Table 2. The data analysis was conducted through a summary table developed by the researchers and it is provided as an additional material in Document S1. The summary table included the basic information about the publications' characteristics and research design as well as the particular information on the studied and/or researched DML aspects and main findings. To tackle RQ1, we extracted the scientific subject, the studied DML domains, the research design attributes, the outcome types, the main findings, and the implications for practice from each paper. The research findings and resultant outcomes were organized for each domain under study: cognitive, social, and affective. The studied cognitive outcomes were conceptual knowledge (CK) and procedural knowledge (PK). The recorded outcomes in the domain of social aspects were qualities and characteristics of collabora \begin{table}
\begin{tabular}{l l} \hline \hline
**Category** & **Description** \\ \hline Reference & Authors and date of study publication \\ Subject & Scientific field or discipline \\ Learning methods & Applied teaching or learning methods \\ DML domain & DML aspect the study focused on: cognitive, social, or affective \\ Research type & Applied research paradigm, e.g., qualitative, quantitative, \\ Research methods & Data collection tools and instruments \\ Participants & Number of participating learners coded in five categories: less \\  & than 10, 10–29, 29–100, 100–499, over 500 \\ Duration & Duration of the learning intervention \\ Results & The overall conclusion on the effect on learning: positive, \\  & negative, or mixed \\ Findings & Cognitive, social, and affective domain DML findings \\ Implications & Practice or policy recommendations in accordance with findings \\  & DML outcome the study focused on in each DML domain: \\  & cognitive, social, or affective Examples: \\ Outcome type & Cognitive outcomes: conceptual, procedural knowledge \\  & Social outcomes: collaboration, social presence, connectedness \\  & Affective outcomes: perceptions, motivation, learning benefits \\ ML attributes supported & Meaningful learning attribute the study confirmed or achieved: \\  & active, constructive, intentional, authentic, cooperative \\ DML support & The degree of SRVE support for deep and meaningful learning: \\  & high, medium, low, none, negative \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Data extraction categories and description. tion (COLL), social presence (SPRES), and connectedness to other participants (CONN). The outcomes in the domain of affective issues were learner perceptions about SVREs (PERC), learner motivation (MOT), and learning benefits (LBs) of SVREs. To answer RQ2, we extracted additional data, namely (i) which of the five attributes of meaningful learning (active, constructive, intentional, authentic, and cooperative) were confirmed or supported by the empirical evidence provided in each study; and (ii) the degree to which SVREs supported DML. The DML support degrees were noted as high, medium, low, none, or negative. To extract data for this category, we used the rubric shown in Table 3. Whenever a study reported a negative result in one domain, this would subsequently lower the total coded DML support degree, taking into account the total aggregate of the results in all domains. In RQ3, we identified and described the many learning effects in each domain. To tackle RQ4, we identified and categorized factors that influence DML and integrated them into a preliminary model. To ensure the reliability of the coded categories, the first author analyzed all studies and the second and third authors each coded half of all included studies.