IAFOR Journal of Education: Technology in Education

Volume 8 – Issue 2 – 2020

Training Factors as Predictors of Students’ Self-Efficacy Beliefs
for Online Journalism PracticeJoseph Njuguna
University of Rwanda
Rwanda141

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Abstract
The advent of Internet technologies has heralded new skill demands in the media industry.
Since journalism education mainly takes its cue from industry trends, media training
institutions are now forced to adjust their curricula and teaching styles to produce online-readygraduates. Drawing on aspects of self-efficacy theory, this correlation study employs aquestionnaire to explore how different training factors influence students’ self-efficacy beliefs
for online journalism work. A sample of 182 mass communication students from five Rwandan
universities participated in the study. Results showed that the training factors explained 29.7%of the variance in the respondents’ self-efficacy beliefs for online journalism work, withpositive correlations between all the training factors and the students’ self-efficacy. In
particular, the types of online skills (β =.069) and availability of teaching facilities (β=.076)
contributed a larger part of the online self-efficacy beliefs than teaching styles (β=.018). These
results showed that training factors have a role in boosting students’ beliefs in their capacity to
execute online journalism tasks in the industry. Results suggested that journalism educators
especially need to enhance different online journalism teaching approaches in order to better
develop future professionals who are online-confident for the workplace.
Keywords: online journalism, self-efficacy, training, pedagogy, Rwanda

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One defining feature of journalism education is the ability of graduates to demonstratecompetence in the changing work environment (Schwalbe, 2009). With Web 2.0 technologies,
professional news production has been transformed as news audiences (called “citizen
journalists”) become active producers and consumers of news, inevitably putting the relevanceof journalism education into sharper focus (Oluchi, 2016). Furthermore, the industry’s gradualinclination towards multi-skilled and techno-savvy graduates has presented a new reality formedia training institutions who are forced to adapt by re-designing their curricula and adopting
better ways of teaching these new skills (Robinson, 2013; Quinn, 2010). Short of this,journalism education risks playing the technological catch-up game as stakeholders continue
to wonder if the institutions are adequately prepared to develop online-ready graduates(Ehreneich, 2009).
Educating the new generation of media professionals requires breaking from traditional
teacher-led approaches by taking cognizance of students’ exposure and agility with the digital
tools they are expected to use in the industry (Patrão & Figueiredo, 2018; Iordache et al., 2017).
With traditional media models almost obsolete, it has been argued that journalism education
can only extricate itself from the crisis of relevance by devising new ways of integrating
technology in the students’ learning experiences. Particularly, the traditional “silo” teaching ofTV, radio and print separately has been challenged, with scholars advocating for an integrativeuse of the technologies to teach these skills for a multimedia environment (Kaul, 2013; Quinn,
2010; Iyer (2015). Harnessing social media tools to co-produce and share story pieces throughclass blogs and Facebook pages are becoming the teaching norm in a number of institutions(Patrão & Figueiredo, 2018). In contrast with traditional journalism pedagogy, co-creation ofstories affords students valuable learning moments, especially through accompanying online
comments to their productions. This teaching approach also scaffolds learners with an active
community of practice enabling them to authenticate their learning experiences (Cindy, 2015;
Ferrucci, 2017).
In online skills training, the nature of content, training approaches and facilities have been
considered crucial in shaping the acquisition of skills for the industry (Iordache et al., 2017;
Iyer, 2015; Jeanti, 2015). In the journalism context, however, research is needed to explore
how students perceive their ability to use these skills at the work place. Some studies have
explored students’ journalistic writing self-efficacy (e.g. Broaddus, 2012) and efficacy beliefs
in social media use (e.g. Patrão & Figueiredo, 2018). Focus on the role of training factors on
students’ online journalism self-efficacy has not been systematically examined. Although
Rwandan journalism schools have integrated the teaching of online journalism skills in theircurricula, it remains unclear how the training contributes to students’ confidence in the use ofsuch skills when they graduate. Hence, this study hopes to fill this void by exploring the roleof content, training approaches and facilities in the students’ self-efficacy beliefs for online
journalism work.
Literature Review
Digital skills are considered critical for professional survival in an increasingly e-permeatedsociety. Indeed, Ferrari (2012) considers digital competence as one of the critical competences
for life-long learning, comprising the “knowledge, skills, attitudes, abilities, …required whenusing digital media to perform tasks …” (p.11). In light of the fast-evolving technologies,
journalism scholars argue that clarity of the variety of online skills required for digital workreadiness among the future professionals is urgently needed (Iyer, 2015; Jeanti, 2015).
However, in the absence of a coherent framework for such skills, Gallardo-Echenique et al.

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Volume 8 – Issue 2 – 2020(2015) suggest that a digital competence framework like Ferrari’s (2012), which amalgamatesother frameworks, can be contextualized to help define the skills expected from media
professionals. This framework expects the 21st century professionals to have skills in social
media communication, creation and distribution of multimedia content, online ethics, online
research and using social media to solve communication problems.
Evidence suggests that skills like online research, multimedia content creation and social media
communication are the cornerstone of modern journalism practice (Jeanti, 2015; Cindy, 2015).
The ability to produce stories for different formats and share them on social media networks
such as blogs, Twitter or news websites has become crucial. Other critical skills gaining
currency include the ability to work with web code and data analytics, as well as crowd
sourcing stories through artificial intelligence-enabled techniques. In essence, the burgeoning
skills call for innovative ways of using the technology to maximize news audience satisfaction(Robinson, 2013; Hirst & Treadwell, 2011).
Journalism educators are urged to tune their training content and techniques by adopting alearning environment that replicates the digital newsroom, which is expected to enhance
students’ digital production skills (Iyer, 2015; Hirst & Treadwell, 2011). Evidence shows that
if social media tools are well appropriated in journalistic training, online story-telling practicesof the future professionals can be enhanced (Aifan, 2015; Hirst & Treadwell, 2011; Quinn(2010). Although a connected multimedia environment with unlimited opportunities forpractice is the ideal for online production skills, leveraging the near-ubiquitous mobile phones
and free online software for editing has sufficed to circumvent the costly equipment in a
number of schools (Salaverría, 2011; Kaul, 2013). Indeed, Bethell (2010) argues thatjournalism students only need a mobile phone and curiosity to produce professional-readystories. Researchers argue that if students have the necessary environment to develop a skill,they will gradually experience confidence and success with the skill and tasks associated withthat skill. Bandura (1986) termed this feeling or belief in their ability to perform a task as one’s
self-efficacy.
While self-efficacy in the context of journalistic performance has largely focused on writing
skills, little attention has been given to new media skills (Broaddus, 2012). Becker et al. (2012)
surveyed the journalism work efficacy of 2,195 US graduating students. More than 70% ofthem attributed the content taught for their self-efficacy for writing and editing for the web,creating blogs, and use of the social media professionally. Wotkyns (2014) explored Australian
university students’ satisfaction of the training environment in a new convergent journalism
major. 88% were extremely-moderately satisfied with the online skills given, indicating thatstudents’ learning expectations were being met. A study by Huang et al. (2020) found thatstudents’ journalistic writing self-efficacy was positively correlated with their actual writing
performance, although the relationship was weak (r =.16), suggesting that their unfamiliarity
with the unique requirements of news writing could have been the cause.
Broaddus (2012) explored how learning strategies (among other factors) contributed to US
journalism majors’ writing self-efficacy. Practical classroom assignments contributed more in
students’ writing self-efficacy than the students’ background experiences and their general
writing background. A linear regression analysis on the extent to which learning experienceswith such scholastic media associated with writing self-efficacy indicated a statisticallysignificant model (F4, 445 = 10.075; p = .000; R2= .075) where newspaper experience (t =3.678; p = .000) and journalism classes (t = 2.671; p = .008) predicted the students’ self-efficacy

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and therefore possible proficiency in writing. It was evident that exposing journalism students
to scholarly media developed their self-efficacy towards producing professional news.
Some studies on technology-focused efficacy indicate a positive relationship between students’technology exposure and usage and their self-efficacy for technology in different academic andprofessional contexts. Shank and Cotton’s (2014) study indicated that students could
vicariously acquire technology self-efficacy from their teachers, implying that educator
characteristics could inculcate beliefs in students’ confident use of technologies. Joo & Choi(2000) explored how students’ Internet self-efficacy related to their Internet research
performance based on written and practical tests. Students’ Internet self-efficacy was related
more to the practical research than to the theoretical test. This was not surprising since handson skills are considered the best test of readiness for work.
Research Context
In Rwanda, periodic media industry surveys have partly attributed the low quality of news
content to poor use of online tools by practitioners. A 2017 Rwanda Governance Board survey
considered poor content as the bane of an industry struggling to stay afloat. About 90% of
media houses’ staff surveyed were confirmed to have inadequate skills for producing
professional stories. Although Rwanda’s media policy (2014-2020) envisaged a citizenry thatis exposed to news through a digitally-empowered media, the 2017 National Media Dialogueechoed a growing stakeholder concern that portrays lackluster use of online tools by media
houses (Mwai, 2017). Journalism schools have largely been criticized for inadequate online
skills development for the industry (Media High Council, 2016). While media training
institutions have increased efforts to train the next generation of “digital journalists”,
stakeholders are still concerned about the nature of online skills taught and techniques
employed (Media High Council, 2016). Although students’ efficacy beliefs for technology use
have been explored in other countries, the role of Rwanda’s journalism training on students’
self-efficacy beliefs for professional online skills is not known. Given that employers expect“online-ready” graduates, the role of such training becomes pertinent.
To understand the role of training factors in the students’ self-efficacy for online journalism
work, the role of content taught, training approaches and training facilities were explored. The
study questions were:
1. How efficacious are Rwandan mass communication students in their online journalism
skills?
2. How does the content taught, training approaches and facilities influence the students’
online journalism self-efficacy beliefs?
3. Are there significant relationships between the training factors and the students’ online
journalism self-efficacy?
The null hypothesis (H0) posited no significant positive relationship between each of the
training factors and the students’ online journalism self-efficacy.
Methods
This study employed a descriptive cross-sectional survey involving a sample of final
undergraduate mass communication students (n=182) drawn from journalism schools in five
Rwandan universities. Yamane’s (1967) formula was used to determine the sample size (i.e.

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for populations of 1500). This sample comprised 98 males and 84 females and together
constituted 62% of the total student journalism and communication student population(n=293). Recruitment of participants was done through a systematic random sampling fromclass lists provided by the heads of the selected schools. Out of the 182 respondents, 143 (79%)
successfully completed and returned the questionnaires.
The survey instrument was developed through an extensive literature review to identify a scale
incorporating components for the training factors and online journalism self-efficacy. Ferrari’s(2012) digital competence framework was adapted to test the students’ self-efficacy beliefs intheir ability to perform the following five online journalism skills: conduct online research;communicate effectively with different social media tools; develop and share multimedia
content; integrate ethical practices in online news publishing; and use social media tools tosolve organizational problems. The respondents indicated their agreement with statements
about training content, teaching style and training facilities and the five online journalism
skills. This was indicated on a five-point Likert-type scale where 1 = Strongly Disagree and 5= Strongly Agree.
To test the quality of the instrument, a pilot survey involving 20 randomly selected students(i.e. four from each journalism school) preceded the main study. The Cronbach Alpha test
indicated an overall instrument reliability score of .79, with factor-wise reliability values
ranging from .072 to .81. Having met the threshold of .07 as recommended (see Faizan andZehra, 2016), the instrument was found fit for the main study.
The gathered data was analysed using SPSS version 21. Descriptive analyses of the responses
showed the patterns of agreements and disagreements with given statements. Inferential
statistics (correlation and regression analyses) were carried out to show the nature andcontribution of the training factors (independent variables) on the students’ efficacy for online
journalism work (dependent variable). Using F-test, the H0 was tested to confirm or disconfirm
the relationship between training factors and students’ efficacy for online journalism. The
hypothesis was tested at a level of significance of 0.05. Results were then used to draw relevant
conclusions of the study.
The research was part of a broader academic study approved by Rwanda’s National Council
for Science and Technology after ethical clearance by the Directorate of Research of the
University of Rwanda. All respondents were informed about their participation rights and theirconsent obtained before commencement. All responses were kept confidential with no identity
required on the questionnaires returned.
Results
Descriptive Analysis of Online Journalism Training Factors
Drawing from empirical research, the training factors considered critical in the development of
online journalism skills included the nature of online skills taught, training style and training
facilities. Mean aggregate responses regarding these factors are summarized in Table 1.
Results showed that having learnt multimedia content production and sharing skills had thehighest mean score (mean=4.11), followed by learning of social media skills (mean=3.99). The
fact that most of the journalism modules taught integrated notions of online skills (e.g.
research) attracted a mean score of 3.69. Furthermore, respondents indicated that content that
related to the industry (e.g. case studies) were well employed in the online journalism classes

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(mean=3.67). These results implied that the respondents had been taught a broad range ofindustry-focused online skills. From the aggregate mean agreement score of 3.87 and standard
deviation of 1.09, respondents generally agreed with the training content despite some slightvariances in their responses.
Table 1: Means and STDVs of training factor responses
Construct
Training
content

Indicator
We learnt some online skills in most of the modules

Mean
3.69

STDV
1.077

We learnt how to use different social media tools
We learnt how to produce and share multimedia content online
We learnt real online case studies from the industry
Sub-variable Aggregate score
Training
Teaching online skills was more practical than theoretical
approach
Online resources like tutorials were sometimes used in teachingSome students volunteered to teach complex online skills like
web design
Lecturers used online tools to professionally interact withstudents
Lecturers demonstrated adequate online journalism skills
Sub-variable Aggregate score
Training
The training facilities (software and hardware) were adequate
facilities
Mobile phones were sometimes used in multimedia production
exercises
Internet connectivity was reliable during online-based classes
Technical support in online journalism classes was always
available
Sub-variable Aggregate score

3.99
4.11
3.67
3.87
4.10

1.051
1.035
1.179
1.09
1.115

3.92
3.73

1.015
1.181

4.22

0.958

3.92
3.98
3.53

1.101
1.07
1.118

4.13

1.013

3.64
3.60

1.178
1.139

3.73

1.112

Overall aggregate score for training factors

3.9

1.1

Being a key component of online journalism education, the prevalence of multimedia
production content and social media skills was not surprising. Scholars argue that journalism
educators need to take cues from the technological advances in the industry and integrate suchskills in the curricula, leveraging social media interactions with the students for professional
teaching and learning (Aifan, 2015; Mihailidis & Shumow, 2011). The results concur withsuggestions for retooling training content in cognizance of most students’ heavy “digital
culture”. By leveraging this digital exposure, scholars argue that trainers would not only savelots of time in teaching already familiar topics but also encourage students to teach themselvesmuch of the emerging content (Ferrucci, 2017; Oluchi, 2016). The high mean score regarding
use of case studies aligned to industry supports researcher recommendations on updating
journalism curricula and employing social media tools in simulated newsrooms for news
production (Iyer, 2015; Hirst & Treadwell, 2011).

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Regarding the approaches to online journalism training, the online interactions between
lecturers and students (e.g. through email and social networking sites) had the highest mean
agreement score (M=4.22, STDV=0.958). This was followed by the lecturers’ use of morepractical than theoretical training approaches like online projects and case studies. (M=4.10,
STDV=1.115) and then the use of free online tutorials to supplement formal teaching ofmultimedia skills like audio or video editing (M=3.92, STDV=1.015). Respondents also
generally considered the trainers as competent and therefore, able to teach the online skills(M=3.92, STDV=1.101). While seemingly recognizing that a number of students were digitalsavvy and therefore could have learnt a number of online skills by themselves, the voluntary
contribution of students in teaching complex topics like web design and development was
acknowledged by most of the respondents (see M=3.73, STDV=1.181).
The results align with studies that suggest the need for journalism educators to adopt pedagogy
strategies that impart the required digital skills for the ever-changing industry. Wotkyns’(2014) study on the level of students’ satisfaction with journalism curricula particularly
highlighted their appreciation with experiential learning approaches that integrated theircreativity and helped to link theory with practice. Jeanti (2015) and Ferrucci (2017) also argue
that teaching digital journalism should be a process where the trainer co-designs the training
with his or her students, allowing for as much innovation as possible. Incorporating students inthe teaching of online skills is also touted as relief for trainers since they are not necessarily
expected to be well-versed with all emerging online tools (Schwalbe, 2009). Results from thecurrent study therefore seem to support this approach where students are taught to largely drive
their own learning through the vast number of online tools.
From the results, mobile phone use in multimedia production training has gained ground in thejournalism schools, with a mean agreement score of 4.13 implying that phones were being used
to supplement the more traditional tools of news production like recorders, cameras andcomputers. The low mean score regarding the adequacy of these traditional training facilities(M=3.53, STDV=1.118) possibly indicated that in the absence of these facilities, the easily
accessible mobile phones came in handy for practical learning purposes. Online journalism
training also seemed to by the availability of reliable internet connection (M=3.64,
STDV=1.178) which is the bedrock of online skills production. To ensure online journalismclasses ran well even in the absence of the lecturers’ interventions, respondents generally
agreed that technical assistance was always available (M=3.60, STDV=1.139). This impliedthat apart from technical assistance from knowledgeable student colleagues, it would seem thatthe training facilities were manned with support staff not only to ensure the facilities wereready for use but also to support students with the online production projects when necessary.
The results concur with other scholarly views on the need for journalism training institutions
to appropriate new media tools that will enhance the online story-telling practices of the future
professionals (Aifan, 2015; Bor, 2014; Wenger & Owen, 2012). As the results show, easy
access to mobile phones as tools of journalistic production can address costs associated withthe traditional journalism equipment (Ferruci, 2017; Salaverría, 2011). Although the ideal
online journalism training facilities are far from being realized (e.g. for reasons of limited
financial means), studies advocate for connected multimedia environments that afford students
with unlimited opportunities to experiment and practice their new media production skills(Alves et al., 2014; Switzer & Switzer, 2013).
Overall, constructs under the training approach had the highest aggregate mean agreementscore among the respondents (M=3.98, STDV=1.07). This was followed by constructs under148

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training content (M=3.87, STDV=1.09) and then constructs under training facilities (M=3.73,
STDV=1.11). The aggregate mean score of all the training factors (M=3.9) indicated that most
respondents generally agreed about the different aspects of the training in online journalism.
The impression created by these results was that students agreed (with moderate variability)that they were trained on a variety of relevant online skills, using innovative techniques which
possibly complemented the traditional teaching approaches and modest online training
facilities. This demonstrates the dynamic nature of online journalism training where scholars
advocate for a keen eye on the evolving digital needs of the media industry coupled withrevised curricula, innovative training and learning techniques and general technical readinessfor a future of technology that is gradually redefining the roles of journalists (Robinson, 2013;
Jeanti, 2015; Tanner, 2014).
Descriptive Analysis of Online Journalism Efficacy
The respondents’ self-efficacy for online journalism was conceptualized as their beliefs in theability to effectively do online journalism research, create and share multimedia stories online,
use social media tools to communicate to different audiences, practice ethical online publishingand solve problems with different online tools. Table 2 shows the aggregated responses under
this variable.
Table 2: Respondents agreement levels on their online journalism efficacy
I believe I can effectively…

Generally Agree(SA+A)
84.4
76.7
73.7

Neutral
(N)
12.1
12.9
15.0

Generally Disagree(D+SD)
3.5
10.3
11.3

Conduct online journalism researchCommunicate with different social media
Create and share multimedia stories
onlineConduct ethical online publishing
80.4
15.0
4.5
Use online tools to solve different
85.3
9.9
4.8
problems
AVERAGE
80.1
13
6.9
Key: SA=Strongly Agree, A=Agree, N=Neutral, D=Disagree, SD=Strongly Disagree

From the results, respondents considered themselves adept in the five online journalism skills,
with an average of more than 80% of them believing they could perform all the skills. The
greatest level of self-efficacy for online journalism was expressed in the ability to use online
tools to solve problems (85.3%), followed by ability to conduct research online (84.4%) andunderstanding of the ethical implications of using online tools (80.4%). Compared to otherdimensions, the respondents had low efficacy for multimedia production skills (73.7%). Only
about 7% of the respondents did not express any efficacy to execute online journalism tasks.
The findings are consistent with studies that explored the digital competence of students. For
example, Sutherland and Ho (2017) and Bethell (2010), argued that digital competence should
best be demonstrated by the ability to identify and solve practical problems. Although scholars
like Switzer & Switzer (2013) and Bor (2014) suggest that students are likely to gain social
media communications skills faster than other skills such as multimedia and problem-solving
skills, this study showed the contrary. It seemed to indicate that the students focused more on
interrogating how social media tools can be used to address problems in organization as well149

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as online research skills than others. To obtain a fuller picture on the relationship between theidentified training factors and the students’ levels of online journalism efficacy, the next section
explores the statistical nature of the relationships as well as contribution of each of the factors
on the students’ online journalism self-efficacy levels.
Correlation Analysis of Training Factors and Online Journalism Efficacy Beliefs
To determine the strength and direction of association between the training factors and thestudents’ self-efficacy for online journalism, correlation analysis was done. The resulting
correlation matrix with correlation coefficients for the aggregate of the training factors andonline journalism efficacy is shown on Table 3.
Table 3: Correlations of training factors and online journalism efficacy
Training factor

Training
content

Trainingstyle

Training
Facilities

Online journalism
self-efficacy

Training contentr1
Sig. (2-tailed)
Training styler.413**
1
Sig. (2-tailed).000
Training Facilities r.489**.419**
1
Sig. (2-tailed)
.000
.000
**
Online journalism r.435.315**.422**
1
self-efficacy
Sig. (2-tailed)
.000
.000
.000
**. Correlation is significant at the 0.01 level (2-tailed); r = Pearson correlation coefficient
Results showed that all the training factors were significant and positively correlated to theonline journalism self-efficacy levels of the students. The nature and types of online skills
taught had the highest significant positive correlation with the students’ online journalism selfefficacy (r=.435, p=.000) followed by training facilities (r=.422, p=0.000). The way online
skills were taught had the least yet significant relationship with the students’ online journalism
self-efficacy (r=.315, p=.000) at 95% level of confidence. The results implied that a unit ofpositive improvement in the nature and types of online skills taught, training facilities andtraining approaches led to a corresponding increase in the students’ online journalism selfefficacy levels by 43.5%, 42.2% and 31.5% respectively. Further, the results disconfirmed theH0 that predicted no significant correlation between training factors and online journalism
efficacy. The observed positive linear relationships supported studies that underscore the needfor journalism schools to adapt their training to the ever-changing media industry if future
professionals were to fit well in the digital industry (Ferrucci, 2017, Ferruci, 2017; Jeanti,2015).
Test of Hypotheses
To explore the statistical significance of the influence of the training factors on the students’
self-efficacy for online journalism, the null hypothesis postulated no significant relationshipbetween the training factors and the online journalism self-efficacy. To test this hypothesis, amultiple regression analysis model was employed to establish if an aggregate mean score of
the training factors could statistically predict the students’ online journalism self-efficacy at
95% level of confidence. The postulated model was fitted thus: Y = β0+ β1X1+ β2X2 +β3X3+Ɛi,
where Y = online journalism self-efficacy, β0 = constant (α = constant term), β1- β3= intercepts

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for the independent variables, X1= training content or online skills taught, X2= training
approaches, X3= training facilities and ε = error term/Stochastic term.
The results in Table 4 presents the fitness of the regression model used in explaining thevariation of online journalism self-efficacy as a result of the identified training factors.
Table 4: Model Summary for training factors on students’ online journalism self-efficacy
Model

1

R

R2

.545a .297

Adjuste
d R2
.282

Std.
Error ofthe
Estimate.474

R Change

Change Statistics
F
df1
df2
ChangeSig. F
Change.297

19.288

.000

2

3

137

a. Predictors: (Constant), Training facilities, Training style, Training content
Results showed that, taken together, all the training factors were highly and significantly
correlated with the students’ online journalism self-efficacy (r=.545, p=.000). Furthermore,
given the coefficient of determination of 0.297 (R2), it was evident that the training factors
exerted some explanatory power on the students’ online journalism self-efficacy. This impliedthat 29.7% of variations in the online journalism efficacy could be explained by the training
factors (on their own in the model). The remaining 70.3% could only be explained by issues
not factored in the model. However, without the constant variable (β0) on the model, thetraining factors had a predictive power of 28.20% (adjusted R2 of .282) on the students’ online
journalism self-efficacy, implying only a minor variation of .015. This adjusted R2 result meantthat a unit improvement of the training factors (without the β0) would improve the students’
self-efficacy for online journalism by a factor of .282 or 28%.
The Analysis of Variance (ANOVA) results (Table 5) indicated that the proposed regression
model had a statistically significant goodness-of-fit at 5% significance, indicated by thecalculated F-statistic of 19.288 which was larger than the critical F-value of 2.67 (obtained
from the F distribution tables) with degrees of freedom (3,140) at p-value<0.000. Moreover,the existence of a significant positive relationship between the training factors and online
journalism efficacy of the students implied that the proposed model could be relied upon todemonstrate the predictive power of training factors on the online journalism efficacy of thestudents.
Table 5: ANOVAa for training factors on students’ online journalism self-efficacy beliefs
Model

Sum ofdf
Mean SquareF
Squares
1 Regression
13.0073
4.336
19.288Residual
30.795
140
.225
Total
43.801
143
a. Dependent Variable: Online journalism self-efficacy
b. Predictors: (Constant), Training Facilities, Training style, Training content

Sig.
.000b

By further testing the significance of the regression coefficients of the training factors on thestudents’ online journalism efficacy (see Table 6), results confirmed a positive relationship151

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between the training content (β=0.059, t=2.780) and training facilities (β=0.076, t=4.058) andthe students’ online journalism self-efficacy, with a significance of .006 and .000 respectively.
Despite the training approaches having indicated a positive relationship with the students’
online journalism efficacy, this relationship was of negligible significance (p>.349)
Table 6: Coefficients for training factorsa
Model

UnstandardizedStandardized
Coefficients
Coefficients
B
Std. Error
Beta
1 (Constant)
2.191
.271
Training content/skills
.059
.021
.236
Training approaches
.018
.019
.077
Training facilities
.076
.019
.346
a. Dependent Variable: Online journalism self-efficacy

t

8.090
2.780
.940
4.058

Sig.

.000
.006
.349
.000

From the results, the proposed model predicting online journalism efficacy from the three
training factors taken together was, therefore, fitted with regression coefficients as follows:
online journalism self-efficacy = 2.191 + 0.059 (training content) + 0.018 (training approaches)+ 0.076 (training facilities) + Ɛ.
With p-values 0.000<0.05 for both training content and training facilities, the H0 was therefore
rejected and a conclusion made that these training factors exerted a significant and positive
influence on the online journalism self-efficacy beliefs of mass communication students in
Rwanda. In an optimal model, however, the H0 for training approaches would be accepted since
it had a p-value>.05, indicating that, though this dimension had a positive relationship withstudents’ self-efficacy for online journalism, its significance did not meet the 95% level ofconfidence. These findings agree with scholarly evidence that advocate for adapting thejournalism training to the required digital content, training approaches and facilities to improvethe career paths of graduates in the digitally-oriented industry (McDevitt & Sindorf, 2012;
Cindy, 2015).
Discussion of Findings
This study sought to explore the relationship between training factors and online journalism
self-efficacy beliefs of mass communication students in Rwanda. The results largely supported
scholarly evidence that training determines the perceived work-preparedness of students.
Respondents generally agreed with the different statements regarding the characteristics ofonline skills offered, the approaches used in teaching these skills as well as the nature offacilities available for teaching and learning online journalism skills. The fact that a good mixof multimedia production and social media skills are well integrated in the curriculum pointed
to alignment of curricula with emerging digital skills in the industry. Of note also were the highmean scores regarding the online skills or content taught as well as the training facilities. This
indicated that Rwandan journalism schools seem to have made appreciable strides in adapting
online tools in the curricula and invested in some facilities to enhance the teaching and learningof these emerging skills.
Correlation analyses showed significant positive correlations between each of the training
factors and online journalism self-efficacy beliefs of the students. This demonstrated that152

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journalism schools cannot ignore the role played by characteristics of training in their quest to
develop online-ready graduates. Media researchers have argued for competence-based training
characterized by teaching skills or content that will make graduates fit well in the workplace(Hirst & Treadwell, 2011). In teaching online skills among the youth such as students, evidenceshows that pedagogy which considers the digital habits of these digital natives might facilitatecompetence development of digital skills which are transferable to the industry (Jeanti, 2015).
In this study, respondents seemed to recognize that some of their colleagues had more advanced
online skills than the lecturers which enabled them to contribute in the teaching and learningof more complex practical exercises like web design and development. This supports
arguments by scholars that in this era of new media technologies, journalism educators should
embrace co-creation of training content and innovative ideas from the learners (Wiebe &McAuley, 2010).
In the context of online journalism education, digital training resources have been considered
key as the rapid development of new technologies requires frequent updates of theinfrastructure (Boers et al., 2012). In this study, though technical facilities had a weak but
positive correlation with the online journalism self-efficacy beliefs of the students, the highmean score regarding the use of mobile phones and online tutorials in the multimedia
production classes gives hope especially with dwindling resources for the more expensive
technical journalism equipment. This is in line with arguments from scholars like Mihailidis
and Shumow (2011) who decry the way some journalism schools compromise practicallearning through “bureaucratic inertia and resource constraints” (p.15) instead of opting forcheaper and more cost-effective alternatives like mobile phones.
The respondents’ good rating on the accessibility to reliable Internet connection and technicalsupport during the training also indicated attempts at technical readiness for the schools
concerned. This augurs well for online skills training since researchers argue that training in
new media technologies require a good mix of tools and techniques all of which depend on theavailability of a reliable source of Internet connectivity (Iyer, 2015; Jeanti, 2015).
By showing that the aggregate mean score of training factors had significant contribution(R2=.297, p<0.05) in the students’ self-efficacy beliefs regarding online journalism work, theregression analysis results demonstrated the central role of these characteristics of training in
explaining or predicting the level of the “online-readiness” of the mass communication
students. Particularly, disaggregated mean scores also indicated that each of the factors had
contribution though with different levels of significance. The findings resonate with studies
that position the revival of journalism curricula and pedagogy techniques as central to theintegration of new media skills in journalism training. Such studies argue for the need forjournalism schools to identify the range of skills or content to be taught and how these will be
continuously and effectively taught in an increasingly dynamic media industry (Tanner, 2014;
Ferrucci, 2017).
Conclusion
The study explored perceptions of mass communication students regarding online skills
training and how these are congruent with their online journalism self-efficacy beliefs. The
respondents expressed agreement in all the factors as characteristic of the online journalism
training in Rwandan journalism schools. This portends well for the development of digitalskills among the future media professionals. In line with previous research, results showed thatthe content taught, how it is taught and the overall training environment were correlated with153

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the students’ self-efficacy for online journalism (Cindy, 2015; Seelig, 2010). In essence, this
implied that improving the quality and diversity of online skills taught and how they aredelivered builds confidence in the students’ ability to use online tools to work in the industry.
Regression analysis also confirmed that the training factors (singly and collectively) positively
contribute to the students’ levels of online journalism self-efficacy, though at varying levels of
statistical significance.
These results are encouraging for online journalism education in Rwanda. However, the study
had some limitations that merit further investigations. Given the narrow focus of the study,
including a combination of other factors beyond training (like field experiences and individual
online behavior) might have produced more insightful results on the self-efficacy of thestudents. Furthermore, the study was limited by the use of a survey. The nuances of the lived
experiences of a phenomenon (in this case, how students make sense of the factors incidental
to their self-efficacy beliefs in online journalism) are best explored with a mixed methods
approach. Including interviews and/or focus group discussions with selected students might
possibly yield a clearer picture of the students’ online journalism self-efficacy beliefs. Despite
these limitations, this study can be considered as an addition to knowledge on how the
dynamics of online journalism training in the digital era are likely to play into building thenecessary confidence for students as they face the increasingly digitally-competitive
workplace.

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Corresponding author: Joseph Njuguna
Contact e-mail: jnjuguna110@gmail.com

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