| Literature DB >> 35992366 |
Kingsley Okoye1, Haruna Hussein1, Arturo Arrona-Palacios2,3, Héctor Nahún Quintero4, Luis Omar Peña Ortega4, Angela Lopez Sanchez5, Elena Arias Ortiz6, Jose Escamilla7, Samira Hosseini1,8.
Abstract
Digital technology and literacy can heighten the transformation of teaching and learning in higher education institutions (HEIs). This study uncovers the extent to which digital technologies have been used to advance the teaching and learning process in HEIs, and the barriers and bottlenecks to why it may not have been effectively implemented across the HEIs. The study used nine selected countries in Latin America (LATAM) based on the main focus of the educators, commercial, and financial investors; to show the level of impact/implications of computer technologies on the teaching and learning processes. We applied a two-step (mixed) methodology (through a quantitative and qualitative lens) for the research investigation, using data collected from survey we administered to faculty members in HEIs across the different countries in LATAM. In turn, we implemented a Text Mining technique (sentiment and emotional valence analysis) to analyze opinions (textual data) given by the participants to help determine challenges and obstacles to using the digital technologies for teaching and learning in the region. Quantitatively, we applied a Kruskal-Wallis H-test to analyze the collected multiple choice and ranked items in the questionnaire in order to identify prominent factors that consummately influence the reach, barriers, and bottlenecks, and where the differences may lie across the different LATAM countries. The results show that the users upheld the emphasis on lack of training, infrastructures and resources, access to internet and digital platforms, as the main challenges to the teaching-learning process. The study also empirically discussed and shed light on critical factors the HEIs, particularly in LATAM, should resolve and adopt in support of the decision-making strategies, operational policies and governance, financial investments, and policymaking, at a time when "digital technologies" have become an inevitable and indispensable part of education and learning.Entities:
Keywords: Digital technologies; Educational innovation; Educational technology; Higher education; LATAM; Learning environments; Technology-Enhanced learning
Year: 2022 PMID: 35992366 PMCID: PMC9376914 DOI: 10.1007/s10639-022-11214-1
Source DB: PubMed Journal: Educ Inf Technol (Dordr) ISSN: 1360-2357
Principal Components Analysis (PCA) with Varimax Rotation factor analysis for the three Constructs (Reach, Barrier, Bottleneck) and survey items
| Principal Components Analysis (PCA) with Varimax Rotation, Eigenvalue > 1 | |||||
|---|---|---|---|---|---|
| Construct (Factor) | Item (question) | Scale | KMO | Bartlett’s Test | |
| Reach | 18,19,24,17,25,26 | Ranked Likert, Multiple-choice | 0.520 | 106.65 | 0.000* |
| Barrier | 16,20,21,22,23 | Ranked Likert, Multiple-choice | 0.514 | 1081.56 | 0.000* |
| Bottleneck | 27,28,29,30,31,32,33,34,35,36 | Ranked Likert, Multiple-choice | 0.704 | 3994.27 | 0.000* |
Significance level: p ≤ 0.05, Items (question) description is provided in Table 5
Correlation of terms or association analysis for the top five most frequently used words broken down by Country
| Correlation of Terms broken down by Country | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Freq. Term | Argentina ( | Brazil ( | Chile ( | Colombia ( | Costa Rica ( | Ecuador ( | Mexico ( | Peru ( | Uruguay( |
Limited (Falta) | Recursos (0.35) Economicos (0.33) Política (0.23) Insumos (0.23) | Preparo (0.68) Aprendizagem (0.68) Tecnológica (0.68) Infraestrutura (0.42) | Digital (0.41) Estímulo (0.38) familiarizarse (0.38) conocimiento (0.38) | Educación (0.36) Claridad (0.33) Pedagogicos (0.33) Formación (0.24) | Conocimiento (0.35) Conectividad (0.35) Capacitación (0.13) Preparer (0.55) | Tecnológica (0.50) Politicas (0.35) Competencias (0.21) Capacitacion (0.21) Internet (0.28) | Tecnológicos (0.19) Capacitación (0.19) Recursos (0.19) Innovación (0.17) | Conocimiento (0.36) Capacidad (0.16) Vision (0.16) Tics (0.16) | No Correlated Term |
Training (Capacitación) | Falta (0.26) Infraestructura (0.21) Accesos (0.20) Cuesta (0.20) | Política (0.68) Acesso (0.68) experiências (0.68) qualidade (0.68) | Calidad (0.29) Costumbre (0.29) Licenciamiento (0.2) Resistencia (0.14) | Reconocimiento (0.24 resistencia (0.10) Faltas (0.24) Institucional (0.24) | Conocimientos (0.2) Recursos (0.41) Utilizada (0.41) Falta (0.13) | Académicas (0.56) Efectiva (0.56) Investigación (0.56) Obligacione s(0.56) Costo (0.13) | Falta (0.19) Motivación (0.16) Infraestructura (0.12) Tradicionalista (0.11) | Resistentes (0.32) Acceso (0.13) Costo (0.21) Falta (0.19) | No Correlated Term |
Access (Acceso) | Softwares (0.33) Tecnológicos (0.27) Internet (0.35) Computadoras (0.19) | No Correlated Term | Tecnologiaśas (0.47) Internet (0.38) Recursos (0.38) Calidad (0.38) | Internet (0.27) Tics (0.28) Aprendizaje (0.22) Económicos (0.16) | Internet (0.66) Servicios (0.37) Aprendizaje (0.37) Plataformas (0.37) | Internet (0.57) Politicas (0.35) Formación (0.21) Tecnológicos (0.35) | Internet (0.36) Tecnológicas (0.36) Herramientas (0.30) Ayudan (0.16) | Equipos (0.39) Capacitacion (0.33) Asesoria (0.30) Economicas (0.30) | No Correlated Term |
Resources (Recursos) | Falta (0.35) Dificultades (0.32) Accesos (0.23) Económicos (0.33) | Financeiros (1) | Internet (0.38) Acceso (0.38) Estudiantes (1) | Suficiente (0.57) Institucional (0.40) Limitacion (0.40) Adquisición (0.40) | Financieros (0.69) Infraestructura (0.69) Costos (0.23) Capacitación (0.23) | Interner (0.57) Plataformas (0.35) Tecnologías (0.21) | Económicos (0.32) Falta (0.19) Infraestructuras (0.1) Limitación (0.16) | Suficientes (0.70) Educativos (0.70) Tecnológicos (0.34) Contenidos (0.49) | No Correlated Term |
Internet (Internet) | Velocidad (0.40) Servicio (0.40) Obstaculo (0.25) Conexión (0.18) | Melhor (1) Acesso (0.68) Qualidade (0.68) capacitaç̃ (0.68) | Acceso (0.40) Computadores (0.38) Calidad (0.38) Velocidad (0.38) Recursos (0.38) | Aprendizajes (0.30) Servicios (0.20) Velocidad (0.28) Acceso (0.27) | Acceso (0.66) Costosas (0.55) Plataformas (0.55) Paradigmas (0.55) Antiguos (0.55) | Acceso (0.57) Plataformas (0.30) Falta (0.28) Permitan (0.35) Políticas (0.39) | Acceso (0.36) Velocidad (0.33) Calidad (0.24) Disponible (0.22) | Servicio (0.42) Accesiblidad (0.38) Lento (0.24) Acceso (0.20) | No Correlated Term |
Cor limit = between 0 to 1 where 0 represents 0% and 1 represents 100% likelihood of the individual terms associated with the corresponding freq. term by country
Level of academic qualifications or degrees of the participants
| Academic qualifications/degrees of the participants | |
|---|---|
| Level | Percentage (%) |
| Bachelors | 26.29% |
| Masters | 47.43% |
| Doctorate | 16.83% |
| Other | 9.46% |
Table showing whether there are strategies for incorporation of digital technology in delivery of the Courses in the HEI
| Integration of digital technologies in delivery of Courses | |
|---|---|
| Level | Percentage (%) |
| Yes | 56.76% |
| No | 11.22% |
| Special occasions | 30.79% |
| No applicable | 1.23% |
Cost of licensing of digital technologies or software for teaching in the HEI
| Cost of licensing of digital technologies and software in delivery of the courses | |
|---|---|
| Level | Percentage (%) |
| High barrier | 42.40% |
| Enough barrier | 30.81% |
| Little barrier | 22.28% |
| Not a barrier | 4.51% |
Fig. 1Demographic distribution of participants based on the gender
Fig. 2Distribution of participants based on number of years or experience within the HEI
Fig. 3Distribution of participants based on their Level of Teaching experience
Fig. 4Distribution of participants based on the School/Discipline
Fig. 5Distribution of participants in terms of whether ICT strategies and support are in place in the HEI
Fig. 6Distribution of participants’ response based on availability of Network and Internet access across the HEI
Fig. 7WordCloud of the top most frequent terms used by the participants to describe the use of digital technologies for teaching and learning in LATAM broken down by Country (the most common terms are listed in Fig. 8)
Fig. 8Chart representing the top most frequent used terms for the collective countries based on Fig. 7
Fragment of the Emotional Valence scores for the different comments provided by the participants towards the use of digital technologies for teaching and learning in LATAM
| Emotional Valence scores for All the LATAM countries | |
|---|---|
| Comments | Valence Score |
| [1] | 0 0 1 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 |
| [20] | -1 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 1 0 0 |
| [39] | 0 -1 1 0 1 0 0 0 0 0 0 0 0 0 2 -1 0 0 0 |
| [58] | -1 0 0 0 -1 0 0 1 0 0 0 0 0 0 0 0 -1 0 1 |
| [77] | 0 0 0 0 -1 0 0 0 0 0 -1 0 0 0 0 2 0 1 0 |
| [96] | 0 0 0 0 0 -1 0 0 1 0 0 0 -1 0 0 0 0 0 0 |
| [115] | 1 -1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 |
| [134] | 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 |
| [153] | 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 |
| [172] | 0 0 0 0 0 0 0 -1 0 0 0 0 0 0 0 0 0 0 0 |
| [191] | 0 0 0 1 -1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 |
| [210] | 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -1 0 0 0 |
Min = -2, Median = 0.00, Mean = 0.04, Max = 3
values = positive ( +), neutral (0), negative (-)
Summary of Emotional Valence scores expressed by the participants broken down by Country
| Emotional Valence scores | ||||
|---|---|---|---|---|
| Country | Min | Median | Mean | Max |
| Argentina | -1.00 | 0.00 | 0.06 | 1.00 |
| Brasil | 0.00 | 0.00 | 0.00 | 0.00 |
| Chile | 0.00 | 0.00 | 0.13 | 2.00 |
| Colombia | -1.00 | 0.00 | 0.07 | 2.00 |
| Costa Rica | -1.00 | 0.00 | -0.09 | 0.00 |
| Ecuador | 0.00 | 0.00 | 0.13 | 1.00 |
| México | -1.00 | 0.00 | 0.07 | 3.00 |
| Perú | -2.00 | 0.00 | -0.05 | 1.00 |
| Uruguay | 0.00 | 0.00 | 0.00 | 0.00 |
| All Countries | -2.00 | 0.00 | 0.04 | 3.00 |
Max-positive ( +), Min/Max-neutral (0), Min-negative (-) values
Fig. 9Chart representing the overall emotions (classification) expressed by the participants across the data (n = 874)
Result of the Kruskal–Wallis H-test considering the research constructs: reach, barrier, and bottleneck
| Kruskal–Wallis test statistics based on the constructs: Reach, Barrier, Bottleneck | ||||
|---|---|---|---|---|
| Construct | Question(Q) | Description | r (X2) | p-value |
Reach (alcance) | 18 | Which of the following technologies do you know that your educational organization explores, is developing or has implemented today? | 19.453 | 0.012* |
| 19 | For what purpose (s) do you use digital technology in your courses? | 9.4526 | 0.305 | |
| 24 | From the following criteria choose those that you take into account to incorporate a digital tool in your courses | 5.9756 | 0.650 | |
| 17 | What are the digital technologies that students require to use for their courses? | 13.381 | 0.099 | |
| 25 | Do you have strategies for incorporating digital technology in the delivery of your courses? | 10.135 | 0.2557 | |
| 26 | Do you use digital technology to collect, analyze, and interpret data on student progress? | 3.0541 | 0.930 | |
Barrier (barrera) | 16 | Do you think that the digital tools available in your educational organization are useful for teaching in the courses you teach? | 14.083 | 0.079 |
| 20 | How prepared do you feel to incorporate digital technology for teaching–learning purposes? | 16.882 | 0.031* | |
| 21 | How well do you know about digital technology applicable to the courses or discipline you teach? | 16.672 | 0.033* | |
| 22 | Do you consider that the cost of licensing digital technology is a factor that makes it difficult to use it in your courses? | 10.535 | 0.229 | |
| 23 | To what extent is the possibility of error or failure of digital technology a factor that you consider when deciding whether or not to use it in your courses? | 14.422 | 0.071 | |
| 37 | In your opinion, what are the obstacles or challenges to using digital technologies for teaching–learning in higher education in LATAM? | - | - | |
Bottleneck (cuello) | 27 | How would you catalog access to the Internet in your educational organization? | 18.58 | 0.017* |
| 28 | Does your educational organization have an Information and Communication Technologies services and support area? | 22.421 | 0.004* | |
| 29 | Does the Department of Information and Communication Technologies report to the highest authority of your educational organization? | 9.0295 | 0.339 | |
| 30 | Is any technological platform used to manage student learning in your organization? Example: LMS—Learning Management System such as Canvas, Blackboard, Google classroom, etc.) | 37.208 | 0.000* | |
| 31 | What is the degree of use of the LMS platform for the management and teaching of your courses? | 8.9616 | 0.345 | |
| 32 | Do you think that the educational organization in which you work has a vision of how students and teachers should use digital technology to improve teaching and learning? | 26.45 | 0.001* | |
| 33 | Is there a training plan on the use of educational technology in your educational organization? | 20.336 | 0.009* | |
| 34 | How effective is the training plan on the use of educational technology? | 8.9848 | 0.343 | |
| 35 | Does the educational organization where I work promote spaces to discuss and plan in a collegial way about the use of digital technology in teaching–learning? | 13.792 | 0.087 | |
| 36 | Does the educational organization where you work give you any incentive or recognition for developing educational innovation projects using digital technology? | 8.7916 | 0.360 | |
Significant level = (*), p-value ≤ 0.05, Confidence Interval (CI) = 95%, df = 8 for nine groups of countries
Post-hoc test considering the variables (constructs) that were pertinent to the use of digital technologies for teaching–learning in HEIs in LATAM by country
| Post-hoc = Dunn (1964) Kruskal Wallis multiple comparison test, p-values adjusted with Bonferroni method | |||||
|---|---|---|---|---|---|
| Construct | Question (Q) | Comparison | Z | Unadjusted p-value | Adjusted p-value |
Reach (alcance) | Q18 | Colombia – Perú** | 3.47414 | 0.00051 | 0.01844 |
| México – Perú** | 3.66743 | 0.00024 | 0.00881 | ||
Barrier (barrera) | Q20 | Argentina – Perú* | 3.09325 | 0.00197 | 0.07127 |
| México – Perú** | 3.67504 | 0.00023 | 0.00856 | ||
| Q21 | Argentina—Perú* | 2.85531 | 0.00429 | 0.15477 | |
| México—Perú** | 3.61557 | 0.00029 | 0.01078 | ||
Bottleneck (cuello) | Q27 | Chile—México* | 2.77124 | 0.00558 | 0.20103 |
| Colombia—México* | 2.34516 | 0.01901 | 0.68467 | ||
| México—Perú* | -2.66068 | 0.00779 | 0.28073 | ||
| Q28 | Argentina—Chile** | -2.44819 | 0.01435 | 0.51686 | |
| Argentina—Colombia** | -3.73620 | 0.00018 | 0.00672 | ||
| Argentina—Costa Rica* | -2.90913 | 0.00362 | 0.13047 | ||
| Argentina—México** | -3.56961 | 0.00035 | 0.01287 | ||
| Argentina—Perú* | -2.24856 | 0.02454 | 0.88344 | ||
| Q30 | Argentina—Chile** | -3.11681 | 0.00000 | 0.06581 | |
| Argentina—Colombia** | -4.00836 | 0.00000 | 0.00220 | ||
| Argentina—México** | -4.02506 | 0.00000 | 0.00205 | ||
| Chile—Perú** | 3.25203 | 0.00000 | 0.04125 | ||
| Colombia—Perú** | 4.08424 | 0.00000 | 0.00159 | ||
| México—Perú** | 4.05093 | 0.00000 | 0.00183 | ||
| Q32 | Brasil—Chile* | 2.63978 | 0.00829 | 0.29864 | |
| Brasil—Ecuador* | 2.64211 | 0.00823 | 0.29660 | ||
| Chile—México* | -3.02394 | 0.00249 | 0.08982 | ||
| Colombia—México* | -2.50936 | 0.01209 | 0.43541 | ||
| Ecuador—México** | -3.19547 | 0.00139 | 0.05025 | ||
| México—Perú* | 2.70152 | 0.00690 | 0.24847 | ||
| Q33 | Argentina—Colombia** | -3.27486 | 0.00105 | 0.03805 | |
| Brasil—Colombia* | -2.32250 | 0.02020 | 0.72740 | ||
| Colombia—Ecuador* | 2.67400 | 0.00749 | 0.26982 | ||
| Argentina—México* | -2.33231 | 0.01968 | 0.70863 | ||
| Brasil—Uruguay* | -2.36463 | 0.01804 | 0.64972 | ||
p ≤ 0.05 Significant Levels = highly sig. (**), slightly sig. (*), see: Table 8 for description of the questions/items (Q)